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I-Corps: Translation Potential of a Low-cost Mechanical Ventilator for Underserved Communities

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Molly Wasko', 'PO_EMAI': 'mwasko@nsf.gov', 'PO_PHON': '7032924749'}

The broader impact of this I-Corps project is based on the development of an innovative and cost-effective mechanical ventilator designed to address critical respiratory needs in low-resource settings. Acute respiratory distress affects about 3 million people annually, with mortality rates reaching 90% in under-resourced areas. This technology aims to save lives, benefiting patients with lung infections and those undergoing some invasive surgeries. With a 71% survival rate among ventilated patients, this solution could substantially elevate survival rates. Additionally, the cost-effectiveness of this solution could provide financial relief to healthcare systems, enabling reallocation of funds to other pressing health issues and fostering a more efficient healthcare system. This project contributes to global health equity, enhancing the quality of care in underserved communities through high-quality, low-cost, practical engineering solutions. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of an innovative and cost-effective mechanical ventilator designed for low-resource communities. The technology focuses on a streamlined mechanical ventilation system that provides continuous respiratory support for patients with acute respiratory distress. The device's reliability, durability, and ease of use, even by non-specialized healthcare workers, are essential functionalities. By excluding unnecessary high-end components, the device remains effective while significantly reducing costs. Technical results from extensive prototype testing demonstrated the ventilator’s ability to deliver consistent and adjustable ventilation to both neonates and adults. Performance evaluations in simulated environments confirmed its efficiency and reliability, showcasing its potential to maintain critical respiratory functions without continuous manual operation. The merit of this project lies in bridging the health resource gap with practical engineering solutions tailored to low-resource constraints.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/29/2024

07/29/2024

None

Grant

47.084

1

4900

4900

2435003

[{'FirstName': 'Emmanuel', 'LastName': 'Akor', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Emmanuel A Akor', 'EmailAddress': 'emmanuel-akor@uiowa.edu', 'NSF_ID': '0000A0BFW', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Kaczka', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David W Kaczka', 'EmailAddress': 'david-kaczka@uiowa.edu', 'NSF_ID': '0000A0B46', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Daniel', 'LastName': 'Meggo', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel Meggo', 'EmailAddress': 'daniel-meggo@uiowa.edu', 'NSF_ID': '0000A0BG1', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'ZipCode': '522421316', 'PhoneNumber': '3193352123', 'StreetAddress': '105 JESSUP HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Iowa', 'StateCode': 'IA', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'IA01', 'ORG_UEI_NUM': 'Z1H9VJS8NG16', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF IOWA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Iowa', 'CityName': 'IOWA CITY', 'StateCode': 'IA', 'ZipCode': '522421320', 'StreetAddress': '2 Gilmore Hall', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Iowa', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'IA01'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435003.xml'}

Collaborative Research: Planning: CHIRRP: Integrating Participatory Urban Modeling and Climate Projections for Community-Driven Flooding Resilience

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Lina Patino', 'PO_EMAI': 'lpatino@nsf.gov', 'PO_PHON': '7032925047'}

Coastal flooding in the Great Lakes region poses significant risks to communities, infrastructure and ecosystems due to fluctuating lake levels, heavy rainfall, and coastal erosion. These stressors that are expected to worsen with climate change are already overwhelming stormwater systems and damaging property. They will also disproportionately affect communities suffering from historical and ongoing socioeconomic disparities and environmental injustices. This project aims to enhance the resilience of Great Lakes coastal cities by co-producing climate information with city practitioners and community-based organizations (CBOs) that can support their decisions to better prevent, prepare and adapt to these stressors. This will be achieved by creating an online participatory tool that integrates climate, hydrological, spatial data and participatory GIS. This decision support tool (DST) called Participatory Urban Modeling and Climate Projections for Community-Driven FlOoding Resilience (PUMP-COR) will be developed with participants in two Great Lakes cities: Benton Harbor (MI) and Milwaukee (WI). It will allow participants to better understand and visualize their risks and make choices that can influence the implementation of solutions. By directly engaging CBOs and city practitioners, this project will broaden and diversify participation in both cities and cultivate more inclusive development decisions that can be generalized to other decisions and geographies.<br/><br/>Specifically, the project will: 1) explore the viability of integrating three existing modeling efforts (across climate, hydrological and spatial information) to inform decision-making that builds the resilience of households, communities, and cities to flooding risks; 2) organize focus groups with CBOs and city practitioners to better understand different definitions and perceptions of resilience, risk, equitable and just solutions, and to provide feedback to each other and to the research team about their preferences and aspirations for PUMP-COR; and 3) build a network of researchers, CBOs, city practitioners, professional associations, and regional organizations to engage in the co-production process for the ongoing project and for a future broader proposal based on what can be learned from the planning grant. This broader proposal and engagement with communities will focus on how online DSTs can increase the number of people, communities and cities using PUMP-COR to build resilience of coastal cities. The outcomes will include improved decision-making for flood resilience, enhanced community participation, and better climate information tailored to the needs of diverse decision-makers. This research will significantly contribute to the fields of climate modeling, participatory GIS, and the science of actionable knowledge, offering innovative solutions for climate adaptation and resilience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/27/2024

08/27/2024

None

Grant

47.050

1

4900

4900

2435004

[{'FirstName': 'Maria Carmen', 'LastName': 'Lemos', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria Carmen M Lemos', 'EmailAddress': 'lemos@umich.edu', 'NSF_ID': '000104036', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jeremy', 'LastName': 'Bricker', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jeremy D Bricker', 'EmailAddress': 'jeremydb@umich.edu', 'NSF_ID': '000819578', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Derek', 'LastName': 'Van Berkel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Derek Van Berkel', 'EmailAddress': 'dbvanber@umich.edu', 'NSF_ID': '000827116', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'ZipCode': '481091079', 'PhoneNumber': '7347636438', 'StreetAddress': '1109 GEDDES AVE, SUITE 3300', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'MI06', 'ORG_UEI_NUM': 'GNJ7BBP73WE9', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MICHIGAN', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Regents of the University of Michigan - Ann Arbor', 'CityName': 'ANN ARBOR', 'StateCode': 'MI', 'ZipCode': '481091079', 'StreetAddress': '440 Church St', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'MI06'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~119770

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435004.xml'}

Collaborative Research: Planning: CHIRRP: Integrating Participatory Urban Modeling and Climate Projections for Community-Driven Flooding Resilience

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Lina Patino', 'PO_EMAI': 'lpatino@nsf.gov', 'PO_PHON': '7032925047'}

Coastal flooding in the Great Lakes region poses significant risks to communities, infrastructure and ecosystems due to fluctuating lake levels, heavy rainfall, and coastal erosion. These stressors that are expected to worsen with climate change are already overwhelming stormwater systems and damaging property. They will also disproportionately affect communities suffering from historical and ongoing socioeconomic disparities and environmental injustices. This project aims to enhance the resilience of Great Lakes coastal cities by co-producing climate information with city practitioners and community-based organizations (CBOs) that can support their decisions to better prevent, prepare and adapt to these stressors. This will be achieved by creating an online participatory tool that integrates climate, hydrological, spatial data and participatory GIS. This decision support tool (DST) called Participatory Urban Modeling and Climate Projections for Community-Driven FlOoding Resilience (PUMP-COR) will be developed with participants in two Great Lakes cities: Benton Harbor (MI) and Milwaukee (WI). It will allow participants to better understand and visualize their risks and make choices that can influence the implementation of solutions. By directly engaging CBOs and city practitioners, this project will broaden and diversify participation in both cities and cultivate more inclusive development decisions that can be generalized to other decisions and geographies.<br/><br/>Specifically, the project will: 1) explore the viability of integrating three existing modeling efforts (across climate, hydrological and spatial information) to inform decision-making that builds the resilience of households, communities, and cities to flooding risks; 2) organize focus groups with CBOs and city practitioners to better understand different definitions and perceptions of resilience, risk, equitable and just solutions, and to provide feedback to each other and to the research team about their preferences and aspirations for PUMP-COR; and 3) build a network of researchers, CBOs, city practitioners, professional associations, and regional organizations to engage in the co-production process for the ongoing project and for a future broader proposal based on what can be learned from the planning grant. This broader proposal and engagement with communities will focus on how online DSTs can increase the number of people, communities and cities using PUMP-COR to build resilience of coastal cities. The outcomes will include improved decision-making for flood resilience, enhanced community participation, and better climate information tailored to the needs of diverse decision-makers. This research will significantly contribute to the fields of climate modeling, participatory GIS, and the science of actionable knowledge, offering innovative solutions for climate adaptation and resilience.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/27/2024

08/27/2024

None

Grant

47.050

1

4900

4900

2435005

[{'FirstName': 'Michael', 'LastName': 'Notaro', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael Notaro', 'EmailAddress': 'mnotaro@wisc.edu', 'NSF_ID': '000176838', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Yafang', 'LastName': 'Zhong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yafang Zhong', 'EmailAddress': 'yafangzhong@wisc.edu', 'NSF_ID': '000721947', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Wisconsin System', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~80230

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435005.xml'}

Planning: CHIRRP: Simulating Coastal Adaptation and Local Exposure for Enhanced Resilience

NSF

10/01/2024

09/30/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Lina Patino', 'PO_EMAI': 'lpatino@nsf.gov', 'PO_PHON': '7032925047'}

Since 1980, the US has experienced more than $2.7 trillion in costs due to climate-related disasters. It includes sea-level rise driven by global climate change, which poses substantial and persistent threats to coastal communities, home to approximately 40% of the nation's population. The projected global and regional sea-level rise predicts elevated risks but lacks local embeddedness, community engagement, and actionability. This project will develop researcher-community partnerships to co-produce a new decision-support toolkit to help visualize, test, and prioritize localized adaptation and mitigation strategies to improve coastal resilience. It will advance knowledge of hazard risk modeling and resilience planning, being rooted in place-based participatory approaches to integrate local stakeholder knowledge and experiences in conceptualizing, designing, and assessing potential solutions, which are fundamental to achieving resilient communities. By engaging frontline organizations in co-development processes, this project will increase cross-sectoral partnerships that will have broader impacts through regional-to-local knowledge translation, develop capacity, and lead to more synergistic resilience policies. It will also include training of graduate student researchers and incorporate lessons into a cross-disciplinary curriculum on sustainability and resilience to reach a larger audience. The project will contribute to broadening participation in higher education and workforce development for next-generation scholars and practitioners.<br/><br/>Within the context of coastal resilience to sea-level rise, there is little evidence-based research on modeling the effects of local adaptation and mitigation policies on hazard risk reduction. This project will provide innovative earth system science modeling tools to examine the dynamic interactions between resilience strategies across different spatial, temporal, and organizational scales and evaluate their expected benefits and trade-offs, with a focus on addressing underlying social inequalities and vulnerabilities. Project activities and methods include: (1) developing equitable partnerships with resilience policymakers in Greater Miami, FL, including local governments and community-based organizations using iterative mapping and snowball sampling methods; (2) deconstructing and mapping the complex network of grey infrastructure and nature-based solutions across spatiotemporal scales and hierarchies using participatory workshop and co-development methods; and (3) rigorously designing and evaluating an integrative dashboard solution using focus groups and research translation workshops to inform modeling frameworks, questions, and social benefits that frame how the project can support pathways to resilience. Ultimately, this project will deliver actionable, science-based solutions to assist policymakers in evaluating the effectiveness of various sea-level rise hazard risk-reduction measures and exploring interactive scenarios and future pathways to enhance community resilience and improve well-being.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/25/2024

08/25/2024

None

Grant

47.050

1

4900

4900

2435008

{'FirstName': 'Sarbeswar', 'LastName': 'Praharaj', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sarbeswar Praharaj', 'EmailAddress': 'spraharaj@miami.edu', 'NSF_ID': '000878672', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'ZipCode': '331462919', 'PhoneNumber': '3052843924', 'StreetAddress': '1320 SOUTH DIXIE HIGHWAY STE 650', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_ORG': 'FL27', 'ORG_UEI_NUM': 'RQMFJGDTQ5V3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MIAMI', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Miami', 'CityName': 'CORAL GABLES', 'StateCode': 'FL', 'ZipCode': '331461155', 'StreetAddress': '1300 Campo Sano Avenue', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '27', 'CONGRESS_DISTRICT_PERF': 'FL27'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~196402

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435008.xml'}

EAGER: Advanced Metasurface Solutions for Powering Battery-Free Biomedical Implants

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Richard Nash', 'PO_EMAI': 'rnash@nsf.gov', 'PO_PHON': '7032925394'}

This project aims to overcome some of the fundamental challenges in the field of implantable medical devices (IMDs) by addressing the critical issue of power source size. Traditional IMDs, such as cardiac pacemakers and neural stimulators, rely on bulky batteries, making them invasive and requiring frequent replacement surgeries. This research proposes an innovative solution using advanced wireless power transfer (WPT) technologies integrated with a novel metasurface slab. The metasurface slab, made of two-dimensional metamaterials with tailored electromagnetic properties, will be attached to the transmitter coil to concentrate electromagnetic fields, thereby increasing efficiency. By enhancing the efficiency of power transmission, this project seeks to enable the development of smaller, battery-free IMDs. These devices promise to reduce surgical invasiveness, minimize postoperative complications, and improve patient outcomes.<br/>The proposed research focuses on two main tasks: designing a metasurface slab to enhance the power transfer efficiency (PTE) of wireless power systems and validating this technology in vivo using rodent models. The metasurface slab will be attached to the transmitter coil to concentrate electromagnetic fields, thereby increasing PTE. This design process will be optimized using a deep learning approach with a conditional deep convolutional generative adversarial network (cDCGAN). The second task involves powering a miniaturized IMD for sciatic nerve stimulation in rodents, demonstrating the practical application and effectiveness of the proposed WPT system. This project leverages advanced AI techniques and aims to significantly improve the feasibility of minimally invasive, miniaturized IMDs, with potential applications across various biomedical fields. The award has the potential to significantly impact multiple research areas, including the development of wireless-powered IMDs for diverse applications, advancements in RFID technology, and innovations within the wearables, Internet of Things (IoT), and Internet of Bodies (IoB) ecosystems. The educational component will integrate research findings into a new undergraduate course, host guest lectures from industry professionals, and provide hands-on research opportunities for high school and undergraduate students. Additionally, students will participate in tours of industry facilities, offering them first-hand exposure to advanced manufacturing processes and hardware design. These efforts will prepare students for careers in biomedical engineering and foster a deep understanding of innovative IMD technologies.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.041

1

4900

4900

2435009

{'FirstName': 'Adam', 'LastName': 'Khalifa', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adam Khalifa', 'EmailAddress': 'a.khalifa@ufl.edu', 'NSF_ID': '000899740', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Florida', 'CityName': 'GAINESVILLE', 'ZipCode': '326111941', 'PhoneNumber': '3523923516', 'StreetAddress': '1523 UNION RD RM 207', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'FL03', 'ORG_UEI_NUM': 'NNFQH1JAPEP3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF FLORIDA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Florida', 'CityName': 'GAINESVILLE', 'StateCode': 'FL', 'ZipCode': '326111941', 'StreetAddress': '1523 UNION RD RM 207', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'FL03'}

{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}

2024~79551

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435009.xml'}

Planning: CHIRRP: Utility of Hyperlocal Flood Data to Co-Advance Urban Flood Knowledge and Mitigation Solutions with Multiple Stakeholders

NSF

11/01/2024

10/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Laura Lautz', 'PO_EMAI': 'llautz@nsf.gov', 'PO_PHON': '7032927775'}

Of the many Earth system hazards that are expected to increase with climate change, urban flooding is one of the most dangerous and costly by negatively impacting public health, safety, infrastructure, and mobility. Multiple stakeholders, including the National Weather Service, city agencies, emergency management teams, community members, and Earth Science researchers, require real-time, quantitative, and accurate data on ongoing and past flood events. To address this need, low-cost water level sensors are being developed by the FloodNet project in New York City to collect, transmit, and provide data on flood depth to stakeholders. The ultimate goal is to make flood data and monitoring tools accessible and useful to stakeholders to ultimately advance flood risk knowledge and mitigation and build community flood resilience. However, there remain open questions related to flood data use by different stakeholders and strategies needed to clean, analyze, and distribute the data to meet desired use cases. The main goal of this planning grant is to develop collaborative partnerships with government agencies, the National Weather Service, and Earth Science researchers, and use the extensive dataset being produced by FloodNet to co-identify and refine research questions aimed at using flood sensor data to better understand and predict urban flooding, as well as implement community-level actions toward adaptation and mitigation. <br/><br/>This project will be conducted through the following objectives: (1) develop and optimize data processing tools to prepare the flood dataset for actionable use; (2) assess desired use cases for flood data at real-time, intermediate, and long-term time scales, and needs for integrating data into existing information systems; and (3) share flood data with stakeholders to co-identify research questions related to flood risk mitigation and needs for design of new tools for data integration and sensemaking, to ultimately co-develop actionable tools and services to aid flood adaptation and mitigation.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/25/2024

08/25/2024

None

Grant

47.050

1

4900

4900

2435015

[{'FirstName': 'Giuseppe', 'LastName': 'Mascaro', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Giuseppe Mascaro', 'EmailAddress': 'Giuseppe.Mascaro@asu.edu', 'NSF_ID': '000703635', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Stanislav', 'LastName': 'Sobolevsky', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stanislav Sobolevsky', 'EmailAddress': 'ss9872@nyu.edu', 'NSF_ID': '000714058', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Andrea', 'LastName': 'Silverman', 'PI_MID_INIT': 'I', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrea I Silverman', 'EmailAddress': 'as10872@nyu.edu', 'NSF_ID': '000734819', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Graham', 'LastName': 'Dove', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Graham Dove', 'EmailAddress': 'gd64@nyu.edu', 'NSF_ID': '000770733', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Charlie', 'LastName': 'Mydlarz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Charlie Mydlarz', 'EmailAddress': 'cm3580@nyu.edu', 'NSF_ID': '000770790', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'New York University', 'CityName': 'NEW YORK', 'ZipCode': '100121019', 'PhoneNumber': '2129982121', 'StreetAddress': '70 WASHINGTON SQ S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'NX9PXMKW5KW8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100121019', 'StreetAddress': '70 WASHINGTON SQ S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~200000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435015.xml'}

Planning: CHIRRP: Engagement and Mitigation for Building Resilience Against Cascading Events in Puerto Rico

NSF

11/01/2024

10/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Lina Patino', 'PO_EMAI': 'lpatino@nsf.gov', 'PO_PHON': '7032925047'}

Interconnected environmental processes influence the initiation and propagation of cascading hazards (e.g., hurricanes, extreme rainfall, floods, landslides) that pose significant risks to infrastructure, ecosystems, and human populations. This threat is particularly acute in underserved communities, which lack sufficient resources, infrastructure, and services to adequately prepare for, respond to, and recover from such hazards. Risk responses at the individual and collective level are hampered not just by a lack of data on the science underlying cascading hazards and specific social and physical vulnerabilities in underserved communities, but by the need for inclusive knowledge formation and decision-making processes. This project collaborates with communities to formulate research questions, conceptualize actionable solutions, and co-produce a research program that advances scientific knowledge, builds community capacity, and reduces vulnerability to the impacts of cascading hazards in a changing climate. While our understanding of cascading hazards shapes the research, there is a need for a strategic shift from response and recovery to preparedness, proactive risk management, and the ability to adapt. This planning project establishes the foundations for enhancing the capacity of geographers, geoscientists, social scientists, and community leaders to effectively evaluate and mitigate the evolving impacts and risks of cascading hazards on underserved communities. Broader impacts include building equitable community partnerships to ensure that the research is grounded in real-world applications and responsive to the needs of the communities it serves, as well as providing interdisciplinary scientific and technical training and experience in community engagement for graduate students.<br/><br/>The overarching goal of this planning project is to lay the groundwork for collaboratively developing a set of fundamental research questions and establishing long-term collaboration in three communities in Puerto Rico to shape and account for the effective investment of federal and local resources. It advances the science, theory, and practice necessary to equitably co-produce project research questions and solutions, and explore dynamic interactions and couplings among natural and social processes affecting the resilience of Puerto Rican communities. First, it contributes to co-production literature by empirically categorizing differing perspectives on how participants view its processes and outcomes. Second, it contributes to Earth system science literature by assessing how sequential hazards may drive one another and how the consequences of cascading hazards may scale temporally and spatially. Third, it extends knowledge on how co-production outcomes may relate to changes in social capital and impact federal and territorial policies and guidance.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/25/2024

08/25/2024

None

Grant

47.050

1

4900

4900

2435016

[{'FirstName': 'James', 'LastName': 'Kinter', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'James Kinter', 'EmailAddress': 'ikinter@gmu.edu', 'NSF_ID': '000567815', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'KL', 'LastName': 'Akerlof', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'KL Akerlof', 'EmailAddress': 'kakerlof@gmu.edu', 'NSF_ID': '000640364', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Alireza', 'LastName': 'Ermagun', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alireza Ermagun', 'EmailAddress': 'aermagun@gmu.edu', 'NSF_ID': '000809109', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Gilberto', 'LastName': 'Guevara', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gilberto Guevara', 'EmailAddress': 'gguevara@prsciencetrust.org', 'NSF_ID': '000855313', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~199052

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435016.xml'}

Planning: CHIRRP: Southern Plains Dry-Line Research and Adaptation Center (SPDRAP)

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

The planning grant develops academic-community partnerships that will advance Earth systems science in the study of regional impacts of climate change. It will do this through the creation of a working group and a series of workshops that prioritize community needs as a result of the shifting dryline in the southern Great Plains – the transition separating aridity zones in the region. Community priorities are integrated into the project through engagement with partners at early stages of the project. Project goals focus on efforts to adapt to and mitigate the effects of the shifting dryline zone. A particular objective of this planning project is to identify community needs and determine which Earth science projects should take priority to be responsive to community interests. <br/><br/>The dryline, which separates the arid western portion of the southern Great Plains (and the US) from the less arid eastern side of the line, has created three zones (arid west, the transition zone, less arid east). Each zone differs in climate, and therefore life, and as climate change shifts the line from west to east, life will need to adjust to these changes in climate. The planning grant is framed on the following three objectives, (1) convene an interdisciplinary working group of academics and community members; (2) co-produce knowledge between community partners and scientists about life along and on either side of the dryline, with an aim to identify Earth science projects and preliminary solution sets that are demonstrably actionable and community-relevant; and (3) coalesce the ideas and guiding principles from community members and academics, via a series of workshops. The shifting dryline has myriad implications for communities located in each of the three zones created by the shifting dryline. This planning grant focuses on shifting patterns of extreme weather (both convective events and extreme temperatures), increases in the size and scope of wildfires, impacts on agricultural practices, impacts on aging electrical grid infrastructure, and the changing economic and cultural characteristics of communities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/27/2024

08/27/2024

None

Grant

47.050

1

4900

4900

2435024

[{'FirstName': 'Hank', 'LastName': 'Jenkins-Smith', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hank C Jenkins-Smith', 'EmailAddress': 'hjsmith@ou.edu', 'NSF_ID': '000084417', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Michael', 'LastName': 'Long', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Michael Long', 'EmailAddress': 'michael.long@okstate.edu', 'NSF_ID': '000589309', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Joseph', 'LastName': 'Ripberger', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joseph Ripberger', 'EmailAddress': 'jtr@ou.edu', 'NSF_ID': '000598112', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jason', 'LastName': 'Furtado', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jason C Furtado', 'EmailAddress': 'jfurtado@ou.edu', 'NSF_ID': '000718038', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mary', 'LastName': 'Foltz', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mary E Foltz', 'EmailAddress': 'mary.foltz@okstate.edu', 'NSF_ID': '000862552', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Oklahoma State University', 'CityName': 'STILLWATER', 'ZipCode': '740781031', 'PhoneNumber': '4057449995', 'StreetAddress': '401 WHITEHURST HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OK03', 'ORG_UEI_NUM': 'NNYDFK5FTSX9', 'ORG_LGL_BUS_NAME': 'OKLAHOMA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oklahoma State University', 'CityName': 'STILLWATER', 'StateCode': 'OK', 'ZipCode': '740781031', 'StreetAddress': '401 WHITEHURST HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OK03'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~139428

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435024.xml'}

Collaborative Research: Planning: Moving beyond vulnerability: Finding earth science solutions to sea-level rise and flooding in small coastal communities

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Laura Lautz', 'PO_EMAI': 'llautz@nsf.gov', 'PO_PHON': '7032927775'}

Saltwater intrusion and sea-level rise (SWISLR) present major challenges for rural and small coastal systems whose residents often need economic and political aid to ameliorate SWISLR issues. Rural and unincorporated areas often do not have the same support as more populated regions due to the lower population densities and constrained planning capacity. Many small coastal communities are economically, culturally, and spiritually connected with their location, making adaptation to SWISLR crucial to maintaining the capacity of these communities to coexist with coastal change. This project works across research institutions, local communities, tribal governments, and municipalities to establish partnerships for understanding local flooding hazards and co-develop science priorities that will directly lead to actionable solutions. <br/><br/>The core activity for this planning grant is to conduct a series of surveys, community workshops, and interviews with stakeholders across Florida (FL) and North Carolina (NC). The goal is to identify specific earth system science problems related to coastal flooding that will lead to detailed, local information for coastal communities. Ultimately, this project will increase the ability of small coastal communities to develop and implement adaptation strategies, while also learning from other communities across the Southeast who are facing similar challenges. This grant advances earth systems hazard research through capitalizing on innovations in high resolution data (remote sensing, machine learning, flood modeling). With these data, this project answers localized questions about the variability of flooding and coastal hazards, moving beyond regional projections to inform local flooding hazards and determine the consequences of a changing system. Bringing new knowledge to overlooked systems and communities will allow understanding of the variability of flooding hazards, determine how understudied areas might contribute new insights to our understanding of SWISLR, and include underserved voices (Indigenous and local communities) in the coastal solutions discussion. Through developing a repository of successful coastal projects and initiating a series of workshops, this project will increase the communication and dissemination of information and stories beyond state lines. This project connects to communities through a co-production process to enhance resilience to SWISLR hazards. Collaboration through FL Sea Grant, NC Sea Grant, and SWISLR Research Coordination Network extends the results of this project throughout municipalities in the southeastern coastal plain. The project deliverables will be openly available and archived as open pre-prints or deposited into open repositories using FAIR data practices.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.050

1

4900

4900

2435030

[{'FirstName': 'John', 'LastName': 'Kominoski', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'John S Kominoski', 'EmailAddress': 'jkominos@fiu.edu', 'NSF_ID': '000314734', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Joy', 'LastName': 'Hazell', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joy E Hazell', 'EmailAddress': 'jhazell@ufl.edu', 'NSF_ID': '0000A0CQX', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Anna', 'LastName': 'Braswell', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Anna E Braswell', 'EmailAddress': 'a.braswell@ufl.edu', 'NSF_ID': '000793232', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Florida', 'CityName': 'GAINESVILLE', 'ZipCode': '326111941', 'PhoneNumber': '3523923516', 'StreetAddress': '1523 UNION RD RM 207', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Florida', 'StateCode': 'FL', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'FL03', 'ORG_UEI_NUM': 'NNFQH1JAPEP3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF FLORIDA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Florida', 'CityName': 'GAINESVILLE', 'StateCode': 'FL', 'ZipCode': '326111941', 'StreetAddress': '1523 UNION RD RM 207', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Florida', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'FL03'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~62999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435030.xml'}

Collaborative Research: Planning: Moving beyond vulnerability: Finding earth science solutions to sea-level rise and flooding in small coastal communities

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Laura Lautz', 'PO_EMAI': 'llautz@nsf.gov', 'PO_PHON': '7032927775'}

Saltwater intrusion and sea-level rise (SWISLR) present major challenges for rural and small coastal systems whose residents often need economic and political aid to ameliorate SWISLR issues. Rural and unincorporated areas often do not have the same support as more populated regions due to the lower population densities and constrained planning capacity. Many small coastal communities are economically, culturally, and spiritually connected with their location, making adaptation to SWISLR crucial to maintaining the capacity of these communities to coexist with coastal change. This project works across research institutions, local communities, tribal governments, and municipalities to establish partnerships for understanding local flooding hazards and co-develop science priorities that will directly lead to actionable solutions. <br/><br/>The core activity for this planning grant is to conduct a series of surveys, community workshops, and interviews with stakeholders across Florida (FL) and North Carolina (NC). The goal is to identify specific earth system science problems related to coastal flooding that will lead to detailed, local information for coastal communities. Ultimately, this project will increase the ability of small coastal communities to develop and implement adaptation strategies, while also learning from other communities across the Southeast who are facing similar challenges. This grant advances earth systems hazard research through capitalizing on innovations in high resolution data (remote sensing, machine learning, flood modeling). With these data, this project answers localized questions about the variability of flooding and coastal hazards, moving beyond regional projections to inform local flooding hazards and determine the consequences of a changing system. Bringing new knowledge to overlooked systems and communities will allow understanding of the variability of flooding hazards, determine how understudied areas might contribute new insights to our understanding of SWISLR, and include underserved voices (Indigenous and local communities) in the coastal solutions discussion. Through developing a repository of successful coastal projects and initiating a series of workshops, this project will increase the communication and dissemination of information and stories beyond state lines. This project connects to communities through a co-production process to enhance resilience to SWISLR hazards. Collaboration through FL Sea Grant, NC Sea Grant, and SWISLR Research Coordination Network extends the results of this project throughout municipalities in the southeastern coastal plain. The project deliverables will be openly available and archived as open pre-prints or deposited into open repositories using FAIR data practices.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.050

1

4900

4900

2435031

{'FirstName': 'Sarah', 'LastName': 'Spiegler', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sarah Spiegler', 'EmailAddress': 'sespiegl@ncsu.edu', 'NSF_ID': '0000A0BD8', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'North Carolina State University', 'CityName': 'RALEIGH', 'ZipCode': '276950001', 'PhoneNumber': '9195152444', 'StreetAddress': '2601 WOLF VILLAGE WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NC02', 'ORG_UEI_NUM': 'U3NVH931QJJ3', 'ORG_LGL_BUS_NAME': 'NORTH CAROLINA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NVH931QJJ3'}

{'Name': 'North Carolina State University', 'CityName': 'Morehead City', 'StateCode': 'NC', 'ZipCode': '285572941', 'StreetAddress': '303 College Circle', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'NC03'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~36999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435031.xml'}

Conference: CSR: NSF Workshop on Quantum Operating Systems Design and Scalable Real-Time Control

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Daniel Andresen', 'PO_EMAI': 'dandrese@nsf.gov', 'PO_PHON': '7032922177'}

Our workshop aims to explore how the emerging quantum systems enable and expand novel Computer Systems Research (CSR) opportunities and promoting cross-disciplinary collaborations. Computer systems researchers possess expertise in building efficient programming environments, modeling and optimizing large-scale systems, and designing architectures for fault tolerance and performance. The workshop will highlight the necessity of rethinking the Quantum Computing (QC) software stack to efficiently process and respond to real-time events and data from quantum hardware. As quantum hardware scales up and becomes more heterogeneous and distributed, the quantum OS will be essential for executing error-correcting kernels, allocating system resources, managing shared quantum memory, and scheduling batch and concurrent programs. The quantum Operating System (OS) is a critical tool for maintaining precision control of large quantum systems and managing quantum resources for practical QC applications.<br/><br/>Recent advancements in QC platforms have not only improved the quantity and quality of qubits but also introduced new capabilities such as mid-circuit measurements and real-time error detection. These advancements open new opportunities for exploring algorithms and quantum error correction protocols, but they also add significant complexity to the control systems and the programming/compilation toolchain. For example, significant improvements are needed in integrating classical high-performance computing resources with QC, developing software for optimizing and executing dynamic quantum circuits, benchmarking and verifying real-time control systems.<br/><br/>As a result, this workshop will inform the CSR community emerging trends of QC technologies and introduce research recommendations to address scalable and reliable software systems to achieve practical QC applications. This workshop will bring together researchers with expert knowledge across algorithms, software, architecture and physical devices to stimulate discussion and foster collaborations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.070

1

4900

4900

2435033

{'FirstName': 'Yongshan', 'LastName': 'Ding', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yongshan Ding', 'EmailAddress': 'yongshan.ding@yale.edu', 'NSF_ID': '000872393', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'ZipCode': '065113572', 'PhoneNumber': '2037854689', 'StreetAddress': '150 MUNSON ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Connecticut', 'StateCode': 'CT', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'CT03', 'ORG_UEI_NUM': 'FL6GV84CKN57', 'ORG_LGL_BUS_NAME': 'YALE UNIV', 'ORG_PRNT_UEI_NUM': 'FL6GV84CKN57'}

{'Name': 'Yale University', 'CityName': 'NEW HAVEN', 'StateCode': 'CT', 'ZipCode': '065118937', 'StreetAddress': '51 Prospect Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Connecticut', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'CT03'}

{'Code': '735400', 'Text': 'CSR-Computer Systems Research'}

2024~90223

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435033.xml'}

EAGER: CHIRRP: Community-driven Tools for Monitoring Flash Droughts to Bolster Resilience in the Agricultural Sector

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Flash drought events, characterized by rapid intensification over a short period, lead to significant socio-economic impacts. These episodes are triggered by complex interactions among multiple factors, including climate and land processes. Recent notable flash droughts have resulted in considerable interest among researchers, state and federal agencies, and various stakeholders. This study aims to engage community members—such as farmers, industry representatives, and county extension agents—who have firsthand experience with the direct impact of flash droughts on agricultural crop yields. Collaboration among researchers, academics, and community leaders is central to this study, which seeks to develop science-based solutions to improve resilience and forecasting, thereby reducing the socio-economic losses faced by farmers, ranchers, and stakeholders due to flash droughts. The outcomes will advance flash drought monitoring and prediction tools, enhancing crop resilience to rapid climate fluctuations. By engaging a wider network of producers, the project aims to deploy effective risk reduction strategies and enhance crop resilience, especially for marginal farmers. These efforts benefit agriculture and food industries by managing the potential impact of flash droughts and fostering regional economic growth.<br/><br/>The project advances the monitoring and forecasting of flash droughts and provides an opportunity to mitigate their impacts by developing a robust flash drought indicator for better monitoring and prediction across various agricultural crops. It quantifies the drivers that trigger flash droughts using a cascade modeling framework to improve seasonal to sub-seasonal predictions. Additionally, it fosters equitable community partnerships to quantify flash drought risks and create actionable solutions to enhance the resilience of the agriculture sector. The results are used to create agricultural extension materials, educational content, and training resources for farmers, aiming to deepen scientific understanding of flash drought risks within the agricultural sector.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/09/2024

08/09/2024

None

Grant

47.050

1

4900

4900

2435046

[{'FirstName': 'Ashok', 'LastName': 'Mishra', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ashok Mishra', 'EmailAddress': 'ashok_mishra@tamu.edu', 'NSF_ID': '000652355', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Ronnie', 'LastName': 'Schnell', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ronnie Schnell', 'EmailAddress': 'ronnie.schnell@ag.tamu.edu', 'NSF_ID': '0000A07ZX', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Texas A&M Engineering Experiment Station', 'CityName': 'COLLEGE STATION', 'ZipCode': '778433124', 'PhoneNumber': '9798626777', 'StreetAddress': '3124 TAMU', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'TX10', 'ORG_UEI_NUM': 'QD1MX6N5YTN4', 'ORG_LGL_BUS_NAME': 'TEXAS A&M ENGINEERING EXPERIMENT STATION', 'ORG_PRNT_UEI_NUM': 'QD1MX6N5YTN4'}

{'Name': 'Texas A&M Engineering Experiment Station', 'CityName': 'COLLEGE STATION', 'StateCode': 'TX', 'ZipCode': '778433124', 'StreetAddress': '3124 TAMU', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'TX10'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435046.xml'}

Travel: Frontiers in Complexity Theory: A Graduate Workshop

NSF

07/01/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Karl Wimmer', 'PO_EMAI': 'kwimmer@nsf.gov', 'PO_PHON': '7032922095'}

The Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) at Rutgers University plans to hold “Frontiers in Complexity Theory: A Graduate Student Workshop” at Rutgers University on July 29–August 1, 2024. The workshop will bring together a large cohort of graduate students working in theoretical computer science to learn about some of the most recent trends in complexity research. The event will be the concluding event of the DIMACS Special Focus on Lower Bounds in Computational Complexity, which is itself part of the DIMACS/Simons Institute Collaboration on Lower Bounds in Computational Complexity. <br/> <br/>The workshop is structured around four “mini-workshops,” each consisting of a series of three two-hour tutorial-style lectures that guide participants from foundational ideas to recent breakthroughs in a current area of complexity theory research. The mini-workshops are: 1) Meta-complexity, 2) Error-correcting Codes, 3) Algebraic Complexity, and 4) Derandomization. Each participant will attend two of the four mini-workshops, attend keynote presentations by the preeminent researchers Avi Wigderson and Ryan Williams, and hear an extended presentation on a recent breakthrough result showing the existence of locally testable codes that have both constant relative distance and rate and are testable with a constant number of queries. By gathering a large cohort of 70-80 graduate students from across the United States and placing them at the forefront of current research in complexity theory, the workshop has the potential to be formative for the relevant generation of complexity theorists, with lasting effects on the field. This award provides accommodations that makes it possible to host these students for the duration of the workshop.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/24/2024

07/24/2024

None

Grant

47.070

1

4900

4900

2435051

[{'FirstName': 'Roy', 'LastName': 'Tell', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Roy Tell', 'EmailAddress': 'roei@cs.toronto.edu', 'NSF_ID': '0000A0C1S', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tamra', 'LastName': 'Carpenter', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tamra J Carpenter', 'EmailAddress': 'tcar@dimacs.rutgers.edu', 'NSF_ID': '000611611', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

{'Code': '779600', 'Text': 'Algorithmic Foundations'}

2024~34940

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435051.xml'}

E-CORE RII: Research Infrastructure Optimization for New Mexico

NSF

09/01/2024

08/31/2028

{'Value': 'Cooperative Agreement'}

{'Code': '01060000', 'Directorate': {'Abbreviation': 'O/D', 'LongName': 'Office Of The Director'}, 'Division': {'Abbreviation': 'OIA', 'LongName': 'OIA-Office of Integrative Activities'}}

{'SignBlockName': 'Jeanne Small', 'PO_EMAI': 'jsmall@nsf.gov', 'PO_PHON': '7032928623'}

This collaborative project is led by the University of New Mexico in collaboration with Navajo Technical University (NTU), New Mexico Tech (NMT), Central New Mexico Community College (CNMCC), and New Mexico State University (NMSU). The Research Infrastructure Optimization for New Mexico (RIO-NM) project seeks to create a more interconnected, inclusive, and innovative research environment. RIO-NM will link the existing research ecosystem in New Mexico with emerging research institutes (ERIs), including Hispanic Serving Institutions (HSIs) and Tribal Colleges and Universities (TCUs). The project focuses on two main areas of need at New Mexico’s ERIs: developing cyberinfrastructure and creation of research pathways. By addressing these needs, RIO-NM will stimulate innovation. In turn, this has potential to lead to economic growth in key sectors resulting in high-value employment opportunities for graduates from ERIs, particularly those from underrepresented groups in science and engineering, thus improving the standard of living in New Mexico. RIO-NM is dedicated to promoting a culture of inclusion and diversity, and expanding participation in the scientific community across various individuals, institutions, and sectors. <br/><br/>The RIO-NM team will focus on three key areas of interconnectivity between New Mexico’s ERIs and its broader research ecosystem: Digital, Human, and Institutional. To achieve this interconnection, RIO-NM will establish two specialized cores: 1) Cyberinfrastructure Core: Focusing on digital and institutional interconnections for ERIs and 2) Research Pathways Core: Connecting researchers, faculty, and students from ERIs with resources and programs statewide. Additionally, an Administrative Core will support overall cohesion and provide administrative assistance. To achieve ERI integration with the state's broader ecosystem, the Cores will employ three mechanisms: 1) Pilot Programs: Initial implementations to test concepts related to cyberinfrastructure and research pathways. 2) Pilot Results Workshops: Statewide workshops to discuss pilot outcomes and encourage adoption by other ERIs and 3) Seed Awards: Funding primarily targeting ERIs for projects in cyberinfrastructure, research pathways, and diversity, equity, and inclusion (DEI). RIO-NM has initially identified four pilot programs, with two topics in the Cyberinfrastructure Core at Navajo Technical University (NTU) and New Mexico Tech (NMT), and two in the Research Pathways Core at Central New Mexico Community College (CNMCC), and New Mexico State University (NMSU). This project is funded by the NSF EPSCoR Collaborations for Optimizing Research Ecosystems (E-CORE) RII Program. The E-CORE RII program supports jurisdictions in building capacity in one or more targeted research infrastructure cores that underlie the jurisdiction’s research ecosystem.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

CoopAgrmnt

47.083

1

4900

4900

2435071

[{'FirstName': 'Lorie', 'LastName': 'Liebrock', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lorie M Liebrock', 'EmailAddress': 'lorie.liebrock@nmt.edu', 'NSF_ID': '000327905', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jason', 'LastName': 'Arviso', 'PI_MID_INIT': 'K', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jason K Arviso', 'EmailAddress': 'jarviso@navajotech.edu', 'NSF_ID': '000515972', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ganesh', 'LastName': 'Balakrishnan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ganesh Balakrishnan', 'EmailAddress': 'gunny@unm.edu', 'NSF_ID': '000516091', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Patricia', 'LastName': 'Sullivan', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Patricia A Sullivan', 'EmailAddress': 'patsulli@nmsu.edu', 'NSF_ID': '000670406', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Philip', 'LastName': 'Lister', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Philip D Lister', 'EmailAddress': 'plister@cnm.edu', 'NSF_ID': '000839586', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'ZipCode': '87131', 'PhoneNumber': '5052774186', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NM01', 'ORG_UEI_NUM': 'F6XLTRUQJEN4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NEW MEXICO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'StateCode': 'NM', 'ZipCode': '87131', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NM01'}

{'Code': '270Y00', 'Text': 'EPSCoR CORE RII'}

2024~4152872

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435071.xml'}

Planning: CHIRRP: Building Collaborations and Capacity to Address Climate Hazards in the Southeast U.S.

NSF

01/01/2025

12/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Lina Patino', 'PO_EMAI': 'lpatino@nsf.gov', 'PO_PHON': '7032925047'}

This project will build collaborations to align academic research with community needs to prepare for Earth system hazards and a changing climate. The project will bring together stakeholders in South Carolina to build capacity for addressing the varied Earth system hazards that the Southeast experiences. These hazards include heat stress in urban and rural settings; flooding from both extreme events and everyday fair-weather periods, where changing tides and rising sea levels amplify the hazard; and pollutant exposures from water and air owing to the rapid residential and industrial growth in the region. To advance Earth system hazard knowledge and risk mitigation across these hazards and in a variety of communities, this project will conduct a coordinated and systematic study to understand these hazards across the region. This project will facilitate meetings to bring communities and academics together and will result in a large-scale proposal to address the hazard concerns that communities identify. Having the community engaged in the process will build trust and literacy in potential solutions and science. The project will build capacity by educating communities during public meetings, training graduate students to collaborate with community and public agency stakeholders and to communicate engineering and scientific information to the public, and incorporating project outcomes into research- and project-based college courses.<br/><br/>This project will form community partnerships that will lead to advances in knowledge of hazards, impacts, and risks in the Earth system and actionable solutions that communities can employ to increase their resilience to these hazards. The communities and organizations that will contribute to this project are already addressing Earth system and climate hazards locally; this project will bring disparate communities together to coordinate efforts on a larger scale. The project will allow academics to engage communities at public meetings, synthesize hazard data in response to the outcomes of those meetings, and co-develop, with community input, actionable solutions to those hazards. This project will coordinate across microclimates, such as the coastal region influenced by the sea breeze circulation, rising sea levels, and extreme weather; the midlands region with long, hot, and humid summers and an increased risk of wildfires under a changing climate; and the upstate region near the foothills of the Appalachian Mountains where it can be more moderate in the summer but has winter season hazards often forgotten.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/27/2024

08/27/2024

None

Grant

47.050

1

4900

4900

2435073

[{'FirstName': 'Pamela', 'LastName': 'Murray-Tuite', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pamela Murray-Tuite', 'EmailAddress': 'pmmurra@clemson.edu', 'NSF_ID': '000495729', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Andrew', 'LastName': 'Metcalf', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew R Metcalf', 'EmailAddress': 'ametcal@clemson.edu', 'NSF_ID': '000667016', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Daniel', 'LastName': 'Kilpatrick', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel J Kilpatrick', 'EmailAddress': 'kilpatdj@mailbox.sc.edu', 'NSF_ID': '000948322', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'ZipCode': '296340001', 'PhoneNumber': '8646562424', 'StreetAddress': '201 SIKES HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'South Carolina', 'StateCode': 'SC', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'SC03', 'ORG_UEI_NUM': 'H2BMNX7DSKU8', 'ORG_LGL_BUS_NAME': 'CLEMSON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Clemson University', 'CityName': 'CLEMSON', 'StateCode': 'SC', 'ZipCode': '296340001', 'StreetAddress': '201 SIKES HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'South Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'SC03'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~200000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435073.xml'}

EAGER: CHIRRP: Responding to Groundwater Depletion and Building Resilience by Examining Emerging Social-Environmental-Technical Structures

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Laura Lautz', 'PO_EMAI': 'llautz@nsf.gov', 'PO_PHON': '7032927775'}

In recent decades, groundwater resources in major U.S. agricultural regions have reached critical levels of depletion. Such significant groundwater depletion causes a multitude of hazards, including agricultural and drinking water shortages, land subsidence, and reduced ecosystem health. Groundwater sustainability is essential for improving the viability of the agricultural sector and for supporting the resilience of farming communities. This project is focused on enhancing the resilience of groundwater resources through a participatory planning approach. Conventional water resources management practices based on Earth system models alone are often insufficient to address these sustainability challenges, partially due to the lack of appropriate tools for engaging stakeholders. To cope with these challenges, the project team will develop an artificial intelligence (AI) based modeling system that empowers farming communities to address groundwater depletion and assess resilience outcomes under different climate and management scenarios. Key research activities include community engagement and AI-based integrated model development to replicate social, hydrological, and technical dynamics in an adaptive groundwater management system. It will directly benefit farming community members by providing new collaborative planning tools for developing groundwater sustainability strategies. <br/><br/>The overarching goal of this project is to create a new paradigm of integrated social-Earth science models that place the community at the center of the design process. The project will develop a semi-structured digital twin (DT) that empowers farming communities to collaboratively tackle groundwater depletion and examine resilience strategies and outcomes under existing and emerging social-environmental-technical structures. The team will develop a graph network to represent the complex topological structures of multifaceted social, hydrological, and technical subsystems, and employ machine learning and deep learning models to simulate intricate hydrological processes and support community planning initiatives. The project will address critical research gaps, including (1) how changes in dynamic interactions among hydrological, climatic, technology use, and irrigation processes affect the equilibrium of groundwater storage, (2) how farming communities effectively participate in collaborative planning and co-design groundwater management strategies, and (3) how research endeavors and community knowledge and priorities can be bridged for actionable solutions to confront groundwater depletion. The project will advance the understanding of groundwater susceptibility and irrigation system resilience to various exogenous and endogenous challenges through the lens of social-environmental-technical systems. By equipping communities with participatory planning tools, the project will facilitate effective groundwater sustainability planning and solution development, enhance scientific communication among stakeholders, and promote responsible groundwater usage for a sustainable and productive future.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/09/2024

08/09/2024

None

Grant

47.050

1

4900

4900

2435082

[{'FirstName': 'Qi', 'LastName': 'Hu', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Qi S Hu', 'EmailAddress': 'qhu2@unl.edu', 'NSF_ID': '000417909', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Christopher', 'LastName': 'Quinn', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher J Quinn', 'EmailAddress': 'cjquinn@iastate.edu', 'NSF_ID': '000691913', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Kofi', 'LastName': 'Akamani', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kofi Akamani', 'EmailAddress': 'k.akamani@siu.edu', 'NSF_ID': '000717657', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ruopu', 'LastName': 'Li', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ruopu Li', 'EmailAddress': 'ruopu.li@siu.edu', 'NSF_ID': '000730537', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Southern Illinois University at Carbondale', 'CityName': 'CARBONDALE', 'ZipCode': '629014302', 'PhoneNumber': '6184534540', 'StreetAddress': '900 S NORMAL AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'IL12', 'ORG_UEI_NUM': 'Y28BEBJ4MNU7', 'ORG_LGL_BUS_NAME': 'BOARD OF TRUSTEES OF SOUTHERN ILLINOIS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Southern Illinois University at Carbondale', 'CityName': 'CARBONDALE', 'StateCode': 'IL', 'ZipCode': '629014302', 'StreetAddress': '900 S NORMAL AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'IL12'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435082.xml'}

Conference: STEM-APWD: Approaches to disability in anthropology

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Tarini Bedi', 'PO_EMAI': 'tbedi@nsf.gov', 'PO_PHON': '7032920000'}

This award supports the convening of a two-day hybrid workshop on approaches to disability across biological, archaeological, and cultural subfields of anthropology, held in association with the 2025 meeting of the Society for Applied Anthropologists. It unites disabled and non-disabled scientists to mutually query the strengths and limitations of current frameworks on disability in anthropology, convening the first anthropology-wide, state-of-the-art conference on disability in anthropology. <br/><br/>Anthropologists are particularly well positioned to leverage the range of scientific and experiential insights that expand the science of disability and the welfare of disabled people. Disability – typically defined as functional impairment (biomedical definition) or poor fit with social structures built for able-bodied individuals (disability studies definition) – affects nearly all people at one time or another. The conference organizers and participants specifically examine the variations of diagnosis, experience, and management of disabilities across individuals, social groups, contexts, and time periods with the aim of developing a closer understanding of this key component of human existence. <br/><br/>The conference results in a number of tangible broader impacts, including: supporting disabled investigators with little or no prior NSF support; supporting students and faculty in EPSCoR jurisdictions and within minority-serving institutions; creating a white paper that describes how to run accessible conferences in anthropology; and broadly disseminating results to academic and non-academic audiences. The outcomes of the conference will be evaluated using a robust evaluation tool to drive targeted dissemination efforts and engagements in the social science of disability. The conference engages junior and senior scholars and seeks to build scientific and publishing and dissemination networks between scholars and to broaden the participation of scientists with disabilities. This project is supported by the Cultural Anthropology, Biological Anthropology, and Archaeology programs.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.075

1

4900

4900

2435084

[{'FirstName': 'Siobhán', 'LastName': 'Cully', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Siobhán M Cully', 'EmailAddress': 'siobhan.mattison@gmail.com', 'NSF_ID': '000201205', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Megan', 'LastName': 'Moodie', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Megan Moodie', 'EmailAddress': 'mmoodie@ucsc.edu', 'NSF_ID': '000615905', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ian', 'LastName': 'Wallace', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ian J Wallace', 'EmailAddress': 'iwallace@unm.edu', 'NSF_ID': '000859242', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'ZipCode': '87131', 'PhoneNumber': '5052774186', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Mexico', 'StateCode': 'NM', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'NM01', 'ORG_UEI_NUM': 'F6XLTRUQJEN4', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NEW MEXICO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of New Mexico', 'CityName': 'ALBUQUERQUE', 'StateCode': 'NM', 'ZipCode': '87131', 'StreetAddress': '1700 LOMAS BLVD NE STE 2200', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Mexico', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'NM01'}

[{'Code': '139000', 'Text': 'Cultural Anthropology'}, {'Code': '139100', 'Text': 'Archaeology'}, {'Code': '139200', 'Text': 'Biological Anthropology'}]

2024~94224

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435084.xml'}

CHIRRP RCN: Catalyzing Flood Justice in the USA

NSF

01/01/2025

06/30/2029

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Laura Lautz', 'PO_EMAI': 'llautz@nsf.gov', 'PO_PHON': '7032927775'}

Flooding is a significant challenge with impacts that are unevenly distributed across communities in the United States. This Research Coordination Network (RCN) addresses the urgent issue of flood injustice by examining the social, economic, and environmental factors that contribute to unequal flood risks and recovery outcomes. Communities of color and those of low socioeconomic status are often disproportionately affected by flooding due to historical inequities and inadequate infrastructure. This project aims to bring together researchers, policymakers, and community organizations to identify and address flood injustice through collaborative research and action. By focusing on interactions between the built environment, natural systems, and social vulnerability, the project seeks to inform public policy and create more equitable flood management strategies, benefiting communities nationwide. It also aims to enhance public understanding of flood risks and empower communities through education and engagement by creating educational opportunities and collaboration among students, researchers, and community members. <br/><br/>The network will synthesize data and insights, catalyze action, and advance knowledge on how flood injustice is shaped by interactions between social, natural, and engineered systems. The project will focus on two main research themes: (1) mechanisms of urban development and climate change that shape flood risk futures; and (2) broadening participation and co-production of place-based research to address flood justice. Key activities include hosting workshops that leverage the thematic expertise of steering committee members, fostering collaboration and knowledge sharing among participants. The network will engage diverse community perspectives by incorporating non-profit organizations and government representatives on the steering committee, facilitating workshops that develop strategies for flood justice. The network will also actively involve graduate students, providing opportunities to engage in convergence research and develop skills necessary for addressing complex social and environmental issues. By advancing the integration of justice into Earth System Science, this project will contribute to more equitable flood mitigation and recovery policies, promoting social equity and resilience in flood-prone communities across the United States. Additionally, by focusing on the role of natural infrastructure in mitigating flood risks and examining the financial and social dynamics of flood risk futures, the project will inform equitable urban planning and policy decisions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/27/2024

08/27/2024

None

Grant

47.050

1

4900

4900

2435089

[{'FirstName': 'Eric', 'LastName': 'Tate', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric C Tate', 'EmailAddress': 'eric.tate@princeton.edu', 'NSF_ID': '000603863', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Beth', 'LastName': 'Tellman', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Beth Tellman', 'EmailAddress': 'btellman@arizona.edu', 'NSF_ID': '000728881', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Marccus', 'LastName': 'Hendricks', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marccus Hendricks', 'EmailAddress': 'mdh1@umd.edu', 'NSF_ID': '000750387', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Antonia', 'LastName': 'Sebastian', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Antonia Sebastian', 'EmailAddress': 'asebastian@unc.edu', 'NSF_ID': '000837931', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Aaron', 'LastName': 'Flores', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aaron B Flores', 'EmailAddress': 'aaron.b.flores@asu.edu', 'NSF_ID': '000938256', 'StartDate': '08/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~500000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435089.xml'}

Your World Is Your Classroom: Equipping Place-Based Laboratories for Student Engagement

NSF

10/01/2024

09/30/2026

{'Value': 'Standard Grant'}

{'Code': '11040100', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'DUE', 'LongName': 'Division Of Undergraduate Education'}}

{'SignBlockName': 'Sonja Montas-Hunter', 'PO_EMAI': 'smontash@nsf.gov', 'PO_PHON': '7032927404'}

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Educational Instrumentation project aims to: 1) create new opportunities for authentic research in the classroom and 2) help students connect to their communities and see science as a part of their world and identity. There is an urgent need to improve STEM classrooms with inclusive teaching practices (e.g. active learning and non-pre-packaged research experiences) while focusing on the societal impacts of STEM. Moreover, today’s students are motivated to solve local issues and serve their communities (Handelsman et al., 2022, Teasdale et al., 2017). Robust, field-ready sensors like the X-ray fluorescence (XRF) and other portable water sensing instrumentation, will support the development new course modules centered on societal issues, such as environmental health and air and water quality, and diversify students' laboratory and data analysis skills. Much of the equipment is portable, enabling field-based research and allowing students to analyze samples they collect, thus expanding their understanding of where and how science can occur. Integrating this equipment into the classroom will benefit all students, particularly those from communities historically excluded from participation in STEM fields. The awardee institution, in particular, is a predominantly women’s college and Hispanic-Serving Institution, where 88% of its students identify as Black, Indigenous, or People of Color (BIPOC). Ultimately, the project will discover if portable environmental lab equipment and place-based modules can boost student engagement, help students view science as a part of their everyday lives, and increase retention in STEM disciplines. <br/><br/>The project is guided by two goals: 1) engage students and help them see that science is a part of their world and community, and 2) retain students in STEM majors. It is anticipated that 160 unique students will engage with the requested equipment over the two-year life of the project and will have multiple opportunities to use the equipment through their coursework. The new equipment will be integrated into two required lower-division and four upper-division electives. This scaffolded engagement will improve technological expertise, discipline knowledge, and increase confidence in asking scientific questions about their environment. To assess engagement and scientific literacy, a retrospective survey for students will be administered after each lab class, at the end of each semester in Years 1 and 2, resulting in four semesters of survey data. The survey will include quantitative questions on a Likert scale to measure the effectiveness and utility of the new equipment, and qualitative questions focusing on the role of Course-Based Undergraduate Research Experience modules in making science feel relevant to their world and community. Institutional data will be used to quantify first- and second-year retention in STEM majors. This project will add to the knowledge base of how place-based active learning modules enhance retention and student engagement. The HSI Program aims to enhance undergraduate STEM education and increase capacity to engage in the development and implementation of innovations to improve STEM learning and teaching at HSIs. Projects supported by the HSI Program will also generate new knowledge on how to achieve these aims.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/12/2024

08/12/2024

None

Grant

47.076

1

4900

4900

2435101

[{'FirstName': 'Adriane', 'LastName': 'Jones', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adriane Jones', 'EmailAddress': 'ajones@msmu.edu', 'NSF_ID': '000700778', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Stacey', 'LastName': 'Peterson', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stacey Peterson', 'EmailAddress': 'speterson@msmu.edu', 'NSF_ID': '000597530', 'StartDate': '08/12/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': "Mount Saint Mary's University", 'CityName': 'LOS ANGELES', 'ZipCode': '900491599', 'PhoneNumber': '2134772899', 'StreetAddress': '12001 CHALON RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '32', 'CONGRESS_DISTRICT_ORG': 'CA32', 'ORG_UEI_NUM': 'CFLWSHQJQ2L7', 'ORG_LGL_BUS_NAME': "MOUNT SAINT MARY'S UNIVERSITY", 'ORG_PRNT_UEI_NUM': None}

{'Name': "Mount Saint Mary's Universtity", 'CityName': 'Los Angeles', 'StateCode': 'CA', 'ZipCode': '900291526', 'StreetAddress': '12001 Chalon Road', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '30', 'CONGRESS_DISTRICT_PERF': 'CA30'}

{'Code': '077Y00', 'Text': 'HSI-Hispanic Serving Instituti'}

2024~176500

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435101.xml'}

SBP: Collaborative Research: Improving Engagement with Professional Development Programs by Attending to Teachers' Psychosocial Experiences

NSF

01/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Steven Breckler', 'PO_EMAI': 'sbreckle@nsf.gov', 'PO_PHON': '7032927369'}

As the U.S. student population grows more diverse, longstanding disparities in educational opportunities and outcomes persist. Efforts to remedy these disparities often use focused professional development (PD) to support educators in more effectively teaching diverse students. PD covers a wide array of topics, such as culturally responsive instruction, inclusive practices for students, and strategies for engaging students who have experienced adversity. What unites these diverse PD approaches is an intentional and explicit focus on understanding the issues facing students with diverse experiences and needs, and on equipping educators with skills to overcome these challenges and support student success. While focused PD is in high demand, little is known about its effectiveness. Many focused PD programs have little to no effect, and some may be counterproductive. For example, these programs can create a sense of psychological threat among educators, leading to feelings of being excluded, judged, or disadvantaged. These outcomes can result in resistance and backlash that undermine program goals.<br/><br/>For focused PD to be successful, it needs to attend to educators' experiences. This project conducts studies that examine how three common sources of psychological threat in focused PDs (identity, culture, and pedagogy threats) shape how educators engage with and use focused PD content in their classrooms, and how this use improves students’ academic experiences and performance. Two studies use focus groups and survey designs to examine these issues among a national sample of educators who have participated in a wide variety of focused PD experiences. Three additional studies use randomized controlled experiments to test strategies for mitigating identity, culture, and pedagogy threats among educators. Together, this work provides insight for creating focused PD environments where all teachers feel valued, equipped to engage with challenging ideas, and capable of growing their classroom skills.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/27/2024

06/27/2024

None

Grant

47.075, 47.076

1

4900

4900

2435115

{'FirstName': 'Stephanie', 'LastName': 'Fryberg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Stephanie Fryberg', 'EmailAddress': 'fryberg@northwestern.edu', 'NSF_ID': '000699620', 'StartDate': '06/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'ZipCode': '602080001', 'PhoneNumber': '3125037955', 'StreetAddress': '633 CLARK ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Illinois', 'StateCode': 'IL', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IL09', 'ORG_UEI_NUM': 'EXZVPWZBLUE8', 'ORG_LGL_BUS_NAME': 'NORTHWESTERN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Northwestern University', 'CityName': 'EVANSTON', 'StateCode': 'IL', 'ZipCode': '602080001', 'StreetAddress': '633 CLARK ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Illinois', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IL09'}

[{'Code': '110Y00', 'Text': 'SBP-Science of Broadening Part'}, {'Code': '133200', 'Text': 'Social Psychology'}, {'Code': '764500', 'Text': 'Discovery Research K-12'}]

2023~310199

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435115.xml'}

Conference: Ninth Conference on Beneficial Microbes

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}

{'SignBlockName': 'Carol Fassbinder-Orth', 'PO_EMAI': 'cfassbin@nsf.gov', 'PO_PHON': '7032928064'}

Scientists increasingly recognize that macro-organisms harbor complex communities of microbes that deeply influence their biology. The Ninth Conference on Beneficial Microbes will provide a forum for the exchange of the latest conceptual and technological developments in the field of host-microbe interactions. The conference will promote inclusion of early career scientists, especially those that have been historically excluded from science. Networking events and interactive poster sessions will be designed with the specific goal of facilitating networking opportunities for early career scientists. <br/><br/>Biologists increasingly recognize that macro-organisms (animals, plants and macro-fungi) are multi-organismal. These associations with microorganisms can have profound implications, such that the phenotype and fitness of animal/plant/fungal hosts can only be understood fully in the context of the microbiome. The study of beneficial microbes is a rapidly advancing field requiring exchange of ideas and methods among scientists working across diverse fields. The Ninth Conference on Beneficial Microbes meeting will provide an overview of the current state of research and future directions of inquiry in the field of host-microbe interactions. The meeting will bring together US and international researchers from multiple disciplines, including microbiology, evolutionary biology, ecology, genomics, developmental biology, immunology, engineering, nutrition and systems biology, who study host-microbe associations across a diversity of systems. The structure and venue of the meeting facilitates networking across scientists and trainee levels, which will spur new ideas and collaborations. Results of the meeting will be disseminated through social media and a published report.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/19/2024

07/19/2024

None

Grant

47.074

1

4900

4900

2435131

{'FirstName': 'Federico', 'LastName': 'Rey', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Federico E Rey', 'EmailAddress': 'ferey@wisc.edu', 'NSF_ID': '000851980', 'StartDate': '07/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'ZipCode': '537151218', 'PhoneNumber': '6082623822', 'StreetAddress': '21 N PARK ST STE 6301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wisconsin', 'StateCode': 'WI', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'WI02', 'ORG_UEI_NUM': 'LCLSJAGTNZQ7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WISCONSIN SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Wisconsin-Madison', 'CityName': 'MADISON', 'StateCode': 'WI', 'ZipCode': '537151218', 'StreetAddress': '21 N PARK ST STE 6301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wisconsin', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'WI02'}

{'Code': '765600', 'Text': 'Symbiosis Infection & Immunity'}

2024~19950

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435131.xml'}

RAPID: The Collapsing Ice and Ocean Ecosystem of Milne Fiord, Canada

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '06090100', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'OPP', 'LongName': 'Office of Polar Programs (OPP)'}}

{'SignBlockName': 'Kelly Brunt', 'PO_EMAI': 'kbrunt@nsf.gov', 'PO_PHON': '7032928457'}

The Canadian Arctic Archipelago hosts a cluster of ice caps and ice fields that amount to 14% of Earth’s total glaciated area. However, a warming ocean and atmosphere is melting the ice and causing it to flow into the ocean at an increasing rate. This is reducing the volume of Earth’s freshwater reservoir, increasing global sea level, and changing the Arctic marine ecosystem. These changes have global societal and environmental implications. This project will study Milne Fiord, which is the final remaining fjord along the northern coast of Ellesmere Island, Canada, with perennial ice cover – a system that is now breaking up. <br/><br/>Milne Fiord hosts a patchwork configuration of sea ice, a marine ice shelf, and a floating glacial ice tongue that covers its sea surface year round. This configuration dams freshwater in the upper water column between floating ice bodies, above their keels, to create a unique epishelf lake ecosystem, where specific organisms reside in a freshwater layer underlain by seawater and separated by a sharp halocline. A calving event in 2020 has triggered rapid changes to this system, which is now breaking up and the epishelf lake is draining. The lake drainage and ice shelf and tongue weakening appears to center around a predominant basal channel in the ice shelf and a set of full-thickness rifts in the ice tongue near the grounding line. A total collapse of this system will result in drainage of the last epishelf lake in Arctic Canada, increased ice-ocean-atmosphere interactions in Milne Fiord, and likely acceleration of the upstream glaciers. This work proposes to test that the long-term increase in atmospheric and oceanic temperatures is increasing basal melting of the Milne ice tongue through increased turbulent ocean heat flux. The project will collect in situ hydrographic profiles and water samples across the fjord. These measurements will be compared with melt rates from phase-sensitive radar to better understand the spatial distribution in ocean forcing and glacial melting in Milne Fiord. These measurements will then be placed into the longer-term context by comparing them to previous hydrographic profiles and mooring timeseries data collected by an ongoing international project between Canadian and US researchers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/15/2024

07/15/2024

None

Grant

47.078

1

4900

4900

2435132

[{'FirstName': 'Britney', 'LastName': 'Schmidt', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Britney E Schmidt', 'EmailAddress': 'britneys@cornell.edu', 'NSF_ID': '000693127', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Peter', 'LastName': 'Washam', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Peter M Washam', 'EmailAddress': 'pw389@cornell.edu', 'NSF_ID': '000832277', 'StartDate': '07/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Cornell University', 'CityName': 'ITHACA', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '341 PINE TREE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'G56PUALJ3KT5', 'ORG_LGL_BUS_NAME': 'CORNELL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Cornell University', 'CityName': 'ITHACA', 'StateCode': 'NY', 'ZipCode': '148502820', 'StreetAddress': '341 PINE TREE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}

{'Code': '528000', 'Text': 'ANS-Arctic Natural Sciences'}

2024~104749

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435132.xml'}

Collaborative Research: e4usa+FIRST: Scaling Collective Impact through Pre-College Robotics Curricula

NSF

09/01/2024

08/31/2027

{'Value': 'Continuing Grant'}

{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}

{'SignBlockName': 'Patricia Simmons', 'PO_EMAI': 'psimmons@nsf.gov', 'PO_PHON': '7032925143'}

This three-year project, Collaborative Research: e4usa + FIRST: Scaling Collective Impact Through Pre-College Robotics Curricula, is housed at the Ohio State University and Arizona State University. The world is rapidly transforming due to technological advancements making the ability to innovate educationally crucial for fostering the next generation of engineers and scientists. This project aims to bridge the gap in pre-college engineering education by developing robust, universally accessible robotics lessons capable of being used as either a stand-alone resource or a complementary resource for existing engineering programs. Partnerships with Engineering for Us All (e4usa) and For Inspiration and Recognition of Science and Technology (FIRST) will leverage and ensure that the resulting engineering curricula will be more accessible to students across diverse urban, suburban, and rural communities. The linkage with industry professionals brings a benefit for teachers and students to promote STEM career opportunities, and possibly strengthen STEM literacy within a more general population. This project has the potential to advance the knowledge and understanding of the feasibility, methodology, and scalability of two successful blended programs to create a new program that is both curricular and co-curricular. The democratization of access to cutting-edge robotics education supports a diverse, well-equipped future workforce to maintain competitive advantages in science and technology.<br/><br/>This three-year project, Collaborative Research: e4usa + FIRST: Scaling Collective Impact Through Pre-College Robotics Curricula, is housed at the Ohio State University and Arizona State University. The project will iteratively develop robotics lessons, teacher guides, and artificial intelligence driven teacher support to achieve nationwide implementation. The project scaffolds engagement with teachers across the nation, building on an initial cohort of 12 high schools. Participating teachers will serve as co-creators and collaborators, with continuous feedback mechanisms to evaluate teachers’ implementation of lessons, impact on student engagement, and scalability of resources. A key strategy is building and securing alliances with academic, non-profit, and industry leaders to foster broad participation. Project activities feature a kick-off workshop, multiple development sprints, summer professional development, an academic year community of practice, mentorship, university and industry partnerships, and scalability and sustainability initiatives. Partnerships among academic institutions, non-profit organizations, industry leaders, and state organizations will allow the project to establish a robust model for integrating robotics into pre-college engineering education, leverage collective resources, and catalyze actions to broaden participation in STEM fields.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/16/2024

08/16/2024

None

Grant

47.041

1

4900

4900

2435174

[{'FirstName': 'Assad', 'LastName': 'Iqbal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Assad Iqbal', 'EmailAddress': 'iqbal29@purdue.edu', 'NSF_ID': '0000A09C9', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Adam', 'LastName': 'Carberry', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Adam R Carberry', 'EmailAddress': 'carberry.22@osu.edu', 'NSF_ID': '000599434', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'ZipCode': '432101016', 'PhoneNumber': '6146888735', 'StreetAddress': '1960 KENNY RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'OH03', 'ORG_UEI_NUM': 'DLWBSLWAJWR1', 'ORG_LGL_BUS_NAME': 'OHIO STATE UNIVERSITY, THE', 'ORG_PRNT_UEI_NUM': 'MN4MDDMN8529'}

{'Name': 'Ohio State University', 'CityName': 'COLUMBUS', 'StateCode': 'OH', 'ZipCode': '432101016', 'StreetAddress': '1960 KENNY RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'OH03'}

{'Code': '136000', 'Text': 'EWFD-Eng Workforce Development'}

2024~135115

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435174.xml'}

Collaborative Research: e4usa+FIRST: Scaling Collective Impact through Pre-College Robotics Curricula

NSF

09/01/2024

08/31/2027

{'Value': 'Continuing Grant'}

{'Code': '07050000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'EEC', 'LongName': 'Div Of Engineering Education and Centers'}}

{'SignBlockName': 'Patricia Simmons', 'PO_EMAI': 'psimmons@nsf.gov', 'PO_PHON': '7032925143'}

This three-year project, Collaborative Research: e4usa + FIRST: Scaling Collective Impact Through Pre-College Robotics Curricula, is housed at the Ohio State University and Arizona State University. The world is rapidly transforming due to technological advancements making the ability to innovate educationally crucial for fostering the next generation of engineers and scientists. This project aims to bridge the gap in pre-college engineering education by developing robust, universally accessible robotics lessons capable of being used as either a stand-alone resource or a complementary resource for existing engineering programs. Partnerships with Engineering for Us All (e4usa) and For Inspiration and Recognition of Science and Technology (FIRST) will leverage and ensure that engineering will be more accessible to students across diverse urban, suburban, and rural communities. The linkage with industry professionals will bring a benefit for teachers and students to promote STEM career opportunities, and possibly strengthen STEM literacy within a more general population. This project has the potential to advance the knowledge and understanding of the feasibility, methodology, and scalability of two successful blended programs to create a new program that is both curricular and co-curricular. The democratization of access to cutting-edge robotics education supports a diverse, well-equipped future workforce to maintain competitive advantages in science and technology.<br/><br/>This three-year project, Collaborative Research: e4usa + FIRST: Scaling Collective Impact Through Pre-College Robotics Curricula, is housed at the Ohio State University and Arizona State University. The project will iteratively develop robotics lessons, teacher guides, and artificial intelligence driven teacher support to achieve nationwide implementation. The project scaffolds engagement with teachers across the nation, building on an initial cohort of 12 high schools. Participating teachers will serve as co-creators and collaborators, with continuous feedback mechanisms to evaluate teachers’ implementation of lessons, impact on student engagement, and scalability of resources. A key strategy is building and securing alliances with academic, non-profit, and industry leaders to foster broad participation. Project activities feature a kick-off workshop, multiple development sprints, summer professional development, an academic year community of practice, mentorship, university and industry partnerships, and scalability and sustainability initiatives. Partnerships among academic institutions, non-profit organizations, industry leaders, and state organizations will allow the project to establish a robust model for integrating robotics into pre-college engineering education, leverage collective resources, and catalyze actions to broaden participation in STEM fields.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/16/2024

08/16/2024

None

Grant

47.041

1

4900

4900

2435175

[{'FirstName': 'Medha', 'LastName': 'Dalal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Medha Dalal', 'EmailAddress': 'medha.dalal@asu.edu', 'NSF_ID': '000844324', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'David', 'LastName': 'Rogers', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'David Rogers', 'EmailAddress': 'd@vidrogers.com', 'NSF_ID': '000955829', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'ZipCode': '852813670', 'PhoneNumber': '4809655479', 'StreetAddress': '660 S MILL AVENUE STE 204', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arizona', 'StateCode': 'AZ', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'AZ04', 'ORG_UEI_NUM': 'NTLHJXM55KZ6', 'ORG_LGL_BUS_NAME': 'ARIZONA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Arizona State University', 'CityName': 'TEMPE', 'StateCode': 'AZ', 'ZipCode': '852813670', 'StreetAddress': '660 S MILL AVENUE STE 204', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arizona', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'AZ04'}

{'Code': '136000', 'Text': 'EWFD-Eng Workforce Development'}

2024~587947

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435175.xml'}

CHIRRP RCN: Building a Community of Practice for Co-Producing Resilient Socio-Ecological Systems in Grasslands

NSF

09/01/2024

08/31/2028

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Tom Evans', 'PO_EMAI': 'tevans@nsf.gov', 'PO_PHON': '7032924891'}

Grasslands are one of the most endangered ecosystems worldwide. Despite losing ~32 million acres since 2012, the Great Plains hosts some of the most intact remaining grasslands. The Great Plains are also one of the most important agricultural regions in the world constituting an at-risk agroecosystem. The Great Plains and other grasslands are vulnerable to land degradation, aquifer drawdown, climate variability and change, leading to water and food insecurity, and risks at the local, national, and international levels to security, health, and wellbeing. A better understanding of human and environmental interactions in the region contributes to more resilient grassland ecosystems and communities. This research coordination network (RCN) develops a community of practice for developing research related to resilient grasslands that incorporates people, the environment, and their interactions. The RCN advances research capacity in grassland regions by building connections and coordinating activities across various stakeholders, including researchers, governments, NGOs, Tribal Nations, resource managers, agricultural producers (farmers, ranchers, etc.) and others who live and work in the Great Plains. The developed frameworks, methods and metrics will lead to generalizable knowledge within the Great Plains and in grasslands in general. The RCN trains K-12 students, as well as undergraduate and graduate students in socio-ecological systems thinking related to resilient grasslands so that future leaders and stakeholders will be better equipped to understand issues, identify solutions, and support implementation of change. The RCN supports virtual and local resilient grassland science fairs, workshops, working groups, virtual cafes, etc. to engage with different audiences. The project produces a Resilient Grasslands toolkit and other co-created deliverables which are shared online for relevant user groups including educators, policy makers, resource managers, and everyday citizens.<br/> <br/>This research coordination network cultivates pathways for multi-stakeholder participation, emphasizing three thematic areas (land, water, and people) and three convergent foci related to resilient grasslands (1- conceptual frameworks, 2- methods, metrics, and infrastructure, and 3- formal/informal education and adaptive co-management). The RCN is designed to achieve three major objectives: 1) Create a Community of Practice to integrate social, ecological, geospatial, and participatory conceptual frameworks for resilient grassland ecosystems and communities, 2) Advance metrics, methods and infrastructure to standardize and co-produce community resilience in grassland regions, 3) Co-develop formal and informal education and “wise use” practices for advancing resilient grasslands by considering people, the environment, and their interactions within systems thinking and adaptive co-management frameworks. Focusing on understudied grassland communities in the Great Plains, the conceptual frameworks, methods, and practices for adaptive co-management. Conceptualizations of land, water, and people across space and time scales advances resilient socio-ecological and human environmental systems thinking, more broadly.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/25/2024

08/25/2024

None

Grant

47.050

1

4900

4900

2435176

[{'FirstName': 'Kristen', 'LastName': 'Baum', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kristen A Baum', 'EmailAddress': 'kbaum@ku.edu', 'NSF_ID': '000242415', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Marcellus', 'LastName': 'Caldas', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marcellus M Caldas', 'EmailAddress': 'caldasma@ksu.edu', 'NSF_ID': '000320812', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jacqueline', 'LastName': 'Vadjunec', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jacqueline M Vadjunec', 'EmailAddress': 'jvadjunec@ou.edu', 'NSF_ID': '000522694', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Rachel', 'LastName': 'Jones', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rachel A Jones', 'EmailAddress': 'rjones@usao.edu', 'NSF_ID': '000920433', 'StartDate': '08/25/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'ZipCode': '730193003', 'PhoneNumber': '4053254757', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OK04', 'ORG_UEI_NUM': 'EVTSTTLCEWS5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Oklahoma Norman Campus', 'CityName': 'NORMAN', 'StateCode': 'OK', 'ZipCode': '730193003', 'StreetAddress': '660 PARRINGTON OVAL RM 301', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OK04'}

{'Code': '297Y00', 'Text': 'CHIRRP: Hzrds & Resilient Plnt'}

2024~499933

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435176.xml'}

IUCRC Planning Grant CUNY Site: Center for Climate Risk Applications CCRA

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': 'bransom@nsf.gov', 'PO_PHON': '7032927792'}

As human-emitted greenhouse gas pollution warms the planet and changes the dynamics of the climate system, losses due to weather extremes and their impacts on human life and property has become a significant and costly challenge. Reliance on historical records with outdated climate states, coarse model resolution, and incongruency between the spatiotemporal scale of impacts exacerbates the problem and presents serious difficulties for the insurance and finance sectors that rely on accurate assessment of natural perils and the corresponding uncertainties around their frequency, intensity, and duration. This knowledge is required to cover climate disaster related losses that, annually, reach well into tens to hundreds of billions of dollars. To address this challenge, three institutions: George Mason University, the Massachusetts Institute of Technology, and the City University of New York have come together to plan an industry-university cooperative research center that addresses the critical, high priority needs of the insurance and finance sectors, both of which are wrestling with uncertainties in assessing risks and damages due to climate-related disasters. Center research thrusts include: (1) improving climate predictions at spatiotemporal scales needed by the insurance and finance industries; (2) modeling the catastrophic impacts of natural perils to critical infrastructure systems; and (3) quantifying how the local environment modifies the frequency, intensity, and impact of weather-related natural perils on people and property. Broader impacts of the Center would include increased national economic stability by providing better and more reliable tools for assessing climate risk; training the next generation of climate science, engineering, and policy professionals able to tackle the challenges that a changing climate poses to the nation; and broadening the diversity of underrepresented groups in climate disaster modeling field.<br/><br/>Research conducted by the Center for Climate Risk Applications, now in the planning phase, will focus on addressing existing gaps on the impact of climate change on a range of natural perils by analyzing state-of-the-art climate model ensembles, improving existing models, and advancing the science of integration between climate modeling and asset-scale risks. Research will analyze and improve the output of climate models at the actionable spatial and temporal scales required by the insurance and finance sectors of the economy. The Center will also develop new methods for downscaling hazard information to asset-scale granularity, while quantifying uncertainties of year-to-decadal climate predictions. Additional work will address the sensitivity of interconnected infrastructure systems to a changing landscape of natural perils and the potential for disruption of critical services and supply/value chains. Natural disasters impact people, not just infrastructure; thus, the Center, presently in the planning stage will also focus on how public policy and regulation impacts the insurance of properties, as well as how existing frameworks for decision-making around these perils inform resilience efforts in the private and public sectors. The Center's education and outreach activities will help enable and maintain healthy insurance and reinsurance markets to promote economic stability and growth in the face of severe threats from climate change to life and property. It will also develop a diverse, knowledgeable, and capable workforce necessary to quantify risks of climate change for those owning assets that need protection as well as the need to improve their ability to understand and predict risks and create policies, standards, and incentives that reduce the risks of loss due to climate change. The City University of New York brings to the Center its decades of experience and expertise in remote sensing, ground observations, urban planning, and hydrology as well as its diverse student body from a wide variety of races and ethnicities that will increase diversity in the climate disaster modeling workforce.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/22/2024

08/22/2024

None

Grant

47.050

1

4900

4900

2435190

[{'FirstName': 'Akira', 'LastName': 'Kawaguchi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Akira Kawaguchi', 'EmailAddress': 'akira@cs.ccny.cuny.edu', 'NSF_ID': '000122948', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Maria', 'LastName': 'Tzortziou', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Maria Tzortziou', 'EmailAddress': 'mtzortziou@ccny.cuny.edu', 'NSF_ID': '000234531', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Marzi', 'LastName': 'Azarderakhsh', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Marzi Azarderakhsh', 'EmailAddress': 'maazarderakhsh@citytech.cuny.edu', 'NSF_ID': '000922139', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Harry', 'LastName': 'Cikanek', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': 'III', 'PI_FULL_NAME': 'Harry A Cikanek', 'EmailAddress': 'hcikanek@ccny.cuny.edu', 'NSF_ID': '000885332', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'CUNY City College', 'CityName': 'NEW YORK', 'ZipCode': '100319101', 'PhoneNumber': '2126505418', 'StreetAddress': '160 CONVENT AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'L952KGDMSLV5', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'CUNY City College', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100319101', 'StreetAddress': '160 CONVENT AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}

{'Code': 'Y17300', 'Text': None}

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435190.xml'}

Conference: NAWEA/WindTech 2024 Graduate Student Symposium at Rutgers: Wind Energy Workforce Engagement and Training

NSF

07/01/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Ron Joslin', 'PO_EMAI': 'rjoslin@nsf.gov', 'PO_PHON': '7032927030'}

This conference proposal requests support for a Graduate Student Symposium (GSS) linked with the North American Wind Energy Academy (NAWEA)/WindTech Conference, with the Symposium scheduled for October 29, 2024. The 2024 GSS, occurring one day prior to the NAWEA/WindTech Conference, serves as an educational forum tailored for graduate and undergraduate students interested in wind energy research and careers. Beyond providing a platform for academic exchange, it endeavors to tackle the pressing necessity of bolstering science communication competencies among students within this domain. This imperative arises from the prevailing societal skepticism, and various challenges encountered in the field of wind energy and broader climate change sciences.<br/><br/>The theme of the 2024 GSS is Wind Energy Workforce Engagement and Training. It aims to provide an enriching and interactive platform for undergraduate and graduate students, helping them hone their communication and networking skills alongside other students and leaders in the fields of wind energy technology, research, and innovation. The inclusion of tutorials on science communication, facilitated by experts from the Alan Alda Center for Communicating Science, will equip students with the necessary skills to effectively convey their research findings to diverse audiences. The GSS builds on, and complements various collaborative efforts (i.e., projects, conferences, and workshops) by the local partner organizations who have been working together since 2021 to ensure a successful transition to offshore wind energy for the State of New Jersey, with regional conferences held at Rutgers University and at Rowan University. The 2024 GSS will primarily serve as a regional event, offering students from institutions in New Jersey, southeastern Pennsylvania, Delaware, Maryland, and southern New York the opportunity to drive to and participate in this single-day event.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/18/2024

07/18/2024

None

Grant

47.041

1

4900

4900

2435195

[{'FirstName': 'Tabbetha', 'LastName': 'Dobbins', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tabbetha A Dobbins', 'EmailAddress': 'dobbins@rowan.edu', 'NSF_ID': '000213616', 'StartDate': '07/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Onur', 'LastName': 'Bilgen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Onur Bilgen', 'EmailAddress': 'o.bilgen@rutgers.edu', 'NSF_ID': '000663077', 'StartDate': '07/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Margaret', 'LastName': 'Brennan-Tonetta', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Margaret F Brennan-Tonetta', 'EmailAddress': 'mbrennan@njaes.rutgers.edu', 'NSF_ID': '000162581', 'StartDate': '07/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Ahmed', 'LastName': 'Aziz Ezzat', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ahmed Aziz Ezzat', 'EmailAddress': 'aziz.ezzat@rutgers.edu', 'NSF_ID': '000814001', 'StartDate': '07/18/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Robert', 'LastName': 'Mieth', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert Mieth', 'EmailAddress': 'robert.mieth@rutgers.edu', 'NSF_ID': '000988648', 'StartDate': '07/18/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

{'Code': '144300', 'Text': 'FD-Fluid Dynamics'}

2024~40020

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435195.xml'}

CAREER: Divergent Transfer Trajectories in Computer Science: A Mixed Methods and Person-Centered Exploration of (In)Equity and Community College Transfer Pathways

NSF

08/01/2024

10/31/2029

{'Value': 'Continuing Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Jeffrey Forbes', 'PO_EMAI': 'jforbes@nsf.gov', 'PO_PHON': '7032925301'}

Northern Arizona University will study transfer pathways from community college to CS majors in the University of California (UC) system to provide the first comprehensive picture of degree and early career trajectories followed by transfer students in CS. Given the financial reward associated with computer science (CS) degrees, increasing diversity in CS majors has important implications for equity within society. One strategy for recruiting a diverse workforce in CS is to build accessible pathways from community colleges to undergraduate CS degree programs. Community college transfer students represent a diverse, high-achieving, and often untapped pool of talented emerging computer scientists. Thus, supporting their success is essential to broadening participation in CS, and future research is needed to understand how community college transfer students navigate their CS degree pathways and obtain success in reaching their educational and professional goals. <br/><br/><br/>This mixed methods study will rely on longitudinal data in the form of surveys, student records, and ethnographic interviews, beginning from the time transfer students enter their UC campus and following them as they matriculate through their CS degree programs. Specific analyses will be guided by two overarching questions: (1) What trajectories do community college transfer students follow in their computer science bachelor’s degree pursuits? (2) How do community college transfer students following varying degree trajectories describe and make meaning of their experiences? Person-centered statistical analyses and ethnographic interviews will also explore variation by gender, race/ethnicity, and socioeconomic background. In particular, this study will add nuance and complexity in terms of how we understand community college transfer student success, pushing us to define success beyond traditional metrics (e.g., degree efficiency; four- or six-year graduation rates; etc.). In doing so, this study will build a more robust knowledge base that can contribute to efforts to advance equity in CS by supporting community college transfer students as they exercise agency throughout their degree programs and obtain their professional goals.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/03/2024

07/03/2024

None

Grant

47.070

1

4900

4900

2435201

{'FirstName': 'Jennifer', 'LastName': 'Blaney', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jennifer M Blaney', 'EmailAddress': 'jennifer.blaney@uga.edu', 'NSF_ID': '000808681', 'StartDate': '07/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Georgia Research Foundation Inc', 'CityName': 'ATHENS', 'ZipCode': '306021589', 'PhoneNumber': '7065425939', 'StreetAddress': '310 E CAMPUS RD RM 409', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'GA10', 'ORG_UEI_NUM': 'NMJHD63STRC5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF GEORGIA RESEARCH FOUNDATION, INC.', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Georgia Research Foundation Inc', 'CityName': 'ATHENS', 'StateCode': 'GA', 'ZipCode': '306021589', 'StreetAddress': '310 E CAMPUS RD RM 409', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'GA10'}

{'Code': '279Y00', 'Text': 'IUSE: Computing Undergrad Educ'}

2024~225684

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435201.xml'}

Travel: NSF Student Travel Grant for the 57th IEEE/ACM International Symposium on Microarchitecture (MICRO 2024)

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Danella Zhao', 'PO_EMAI': 'dzhao@nsf.gov', 'PO_PHON': '7032924434'}

The International Symposium on Microarchitecture (MICRO), sponsored by the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM), is widely recognized as a premier forum for disseminating cutting-edge ideas and innovations in the field of computer architecture. MICRO brings together a diverse group of researchers in areas spanning computer hardware/software/hybrid design, systems, chips, and compilers to facilitate interactions and advance the state-of-the-art in computing research and emerging areas. This grant seeks to broaden student participation at MICRO 2024 to be held in Austin, Texas on November 2-6 along with a series of co-located workshops on related topics. The travel fund will provide students with valuable exposure to new ideas and opportunities to engage with leading experts in their fields. It will advance computer systems design education and research in academia, cultivating a strong workforce to tackle the intersection of technological and societal problems that lie ahead. <br/><br/>This award will provide travel support for at least 25 US-based students attending MICRO 2024 by helping defray a portion of their travel, lodging, and attendance expenses. Each awardee will receive approximately $600 of support, subject to their individual needs. This fund especially focuses on increasing institutional, geographic, and demographic diversity and balances the participation of students who are first-time attendees, lack existing travel support, women, underrepresented group members, and students with disabilities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/12/2024

07/12/2024

None

Grant

47.070

1

4900

4900

2435217

{'FirstName': 'Minesh', 'LastName': 'Patel', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Minesh Patel', 'EmailAddress': 'mp2099@rutgers.edu', 'NSF_ID': '0000A08Z2', 'StartDate': '07/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'ZipCode': '089018559', 'PhoneNumber': '8489320150', 'StreetAddress': '3 RUTGERS PLZ', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'M1LVPE5GLSD9', 'ORG_LGL_BUS_NAME': 'RUTGERS, THE STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rutgers University New Brunswick', 'CityName': 'NEW BRUNSWICK', 'StateCode': 'NJ', 'ZipCode': '089018559', 'StreetAddress': '3 RUTGERS PLZ', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

{'Code': '779800', 'Text': 'Software & Hardware Foundation'}

2024~15000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435217.xml'}

Conference: The KOI Combinatorics Lectures

NSF

09/01/2024

08/31/2027

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Stefaan De Winter', 'PO_EMAI': 'sgdewint@nsf.gov', 'PO_PHON': '7032922599'}

The 3rd KOI Combinatorics Lectures will be held October 4-5, 2024 at Indiana University. This regional conference is organized by members of the combinatorics community from the Kentucky, Ohio and Indiana (KOI) area. It seeks to rebuild and initiate research connections among the KOI area graduate students, postdocs and faculty, including individuals from over thirty nearby small colleges, regional universities and ethnically diverse colleges. The conference program consists of four talks from emerging and established researchers in combinatorics broadly defined, a problem session, and a poster session that is open to all participants. In Japanese culture, koi symbolize strength, courage, patience and success through perseverance. All of the conference activities serve to strengthen these attributes among the participants, with a strong focus on increasing the numbers of underrepresented groups in the mathematical sciences, including women. The follow-up yearly conferences will continue at the University of Kentucky in 2025 and the Ohio State University in 2026.<br/><br/><br/>The KOI Combinatorics Lectures showcase national and internationally recognized researchers in combinatorics. New developments in combinatorics and its interactions with other mathematical fields including algebraic geometry, algebra, topology, and artificial intelligence, will be featured. Interactions among all of the participants and the speakers, as well as learning the latest progress and techniques in the field of combinatorics, have the potential to contribute to the growing connections between combinatorics and other scientific areas, including physics, computer science and biology. The vertical mentoring, inclusion of educational activities, and recruitment of speakers and participants from a broad range of institutions and backgrounds contribute to the engagement, retention and equity goals of the NSF. Further details about the conference may be found on the website https://sites.google.com/view/koicombinatorics/<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/19/2024

08/19/2024

None

Grant

47.049

1

4900

4900

2435236

[{'FirstName': 'Saul', 'LastName': 'Blanco Rodriguez', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Saul A Blanco Rodriguez', 'EmailAddress': 'sblancor@iu.edu', 'NSF_ID': '000951138', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Mihai', 'LastName': 'Ciucu', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mihai A Ciucu', 'EmailAddress': 'mciucu@indiana.edu', 'NSF_ID': '000318478', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Margaret', 'LastName': 'Readdy', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Margaret A Readdy', 'EmailAddress': 'margaret.readdy@uky.edu', 'NSF_ID': '000193114', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Richard', 'LastName': 'Ehrenborg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Richard Ehrenborg', 'EmailAddress': 'richard.ehrenborg@uky.edu', 'NSF_ID': '000101176', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Eric', 'LastName': 'Katz', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Eric Katz', 'EmailAddress': 'katz.60@osu.edu', 'NSF_ID': '000572446', 'StartDate': '08/19/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Indiana University', 'CityName': 'BLOOMINGTON', 'ZipCode': '474057000', 'PhoneNumber': '3172783473', 'StreetAddress': '107 S INDIANA AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'IN09', 'ORG_UEI_NUM': 'YH86RTW2YVJ4', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF INDIANA UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Indiana University', 'CityName': 'BLOOMINGTON', 'StateCode': 'IN', 'ZipCode': '474057106', 'StreetAddress': '831 East 3rd St.', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'IN09'}

{'Code': '797000', 'Text': 'Combinatorics'}

2024~15260

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435236.xml'}

Analytic Number Theory over Function Fields

NSF

02/15/2024

06/30/2024

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Andrew Pollington', 'PO_EMAI': 'adpollin@nsf.gov', 'PO_PHON': '7032924878'}

Number theory is an area of mathematics that centers on the ordinary counting numbers and their behavior when we add and multiply them. While problems in this area are often simple to state, they can be fiendishly difficult to solve. The subfield of function field number theory aims to obtain insight on these problems by considering a kind of model or parallel universe where numbers behave differently. We consider what happens when we add or multiply numbers as normal but, except, instead of carrying digits, we simply drop the excess. Certainly arithmetic is a little easier with this modified rule, but more surprisingly, some of the most important problems in number theory become easier as well, with even some of the most difficult ones becoming solvable. (Technically, we should work in binary, or any prime base, rather than our usual base 10, for this.) Alternately, we can describe this variant arithmetic as the addition or multiplication of polynomial functions in a single variable. In this setting, we can connect number-theoretic questions to geometry, by viewing the graph of the polynomial as a geometric object. In this award the PI's research uses geometric tools to solve new problems in this area.<br/><br/>The PI's research has resolved function field analogues of classical problems in number theory, including the twin primes conjecture and Chowla's conjecture (both joint with Shusterman), cases of the Ramanujan conjecture (joint with Templier), and conjectures about moments of L-functions. In this award the PI will continue along these lines, proving additional results about the distribution of prime numbers, L-function moments, and automorphic forms, and work in further directions such as non-abelian Cohen-Lenstra heuristics. These works are all based on etale cohomology theory, where the foundational result, Deligne's Riemann Hypothesis, allows many different analytic problems (problems about proving some inequality) to be reduced to cohomology problems (problems about calculating some of the cohomology groups of a variety or sheaf). The relevant varieties are high-dimensional, and calculating the necessary cohomology groups requires techniques like vanishing cycles theory and the characteristic cycle.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/12/2024

06/12/2024

None

Grant

47.049

1

4900

4900

2435243

{'FirstName': 'Will', 'LastName': 'Sawin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Will Sawin', 'EmailAddress': 'sawin@math.columbia.edu', 'NSF_ID': '000832198', 'StartDate': '06/12/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'ZipCode': '085442001', 'PhoneNumber': '6092583090', 'StreetAddress': '1 NASSAU HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New Jersey', 'StateCode': 'NJ', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'NJ12', 'ORG_UEI_NUM': 'NJ1YPQXQG7U5', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF PRINCETON UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Princeton University', 'CityName': 'PRINCETON', 'StateCode': 'NJ', 'ZipCode': '085442001', 'StreetAddress': '1 NASSAU HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New Jersey', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'NJ12'}

{'Code': '126400', 'Text': 'ALGEBRA,NUMBER THEORY,AND COM'}

2023~24864

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435243.xml'}

EAGER: Analysis of Workforce Supply Chains for Emerging Technology Areas

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '15020000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'ITE', 'LongName': 'Innovation and Technology Ecosystems'}}

{'SignBlockName': 'Rebecca Shearman', 'PO_EMAI': 'rshearma@nsf.gov', 'PO_PHON': '7032927403'}

U.S. policy is spurring a range of ambitious public and private investments that seek to improve national industrial capacity, economic security, and competitiveness – large-scale capacity investments will create thousands of new jobs, often in occupations without a significant base of current employment in the regions where investments are made. Meeting this new demand for skills will require policymakers, employers and trainers to identify other occupations that partially meet new job requirements, and to quantify what skills may be needed for workers to transition into new opportunities. This project will develop and improve methods to help evaluate the potential readiness of regional workforces to meet the skill demand created by large-scale industry transitions. This project will also help produce capabilities that can provide insight into possible transition opportunities for workers whose employment may be disrupted by technological and economic transformation.<br/><br/>Firms, trainers, government, labor groups and other key decision-makers lack consistent, data-driven methods for evaluating workforce feasibility. Rather than a one-time study for a specific project or technology, a flexible and repeatable capability is needed for decision-support across a range of industrial scenarios, to identify for any given investment proposal the conditions under which that proposal may be feasible from a workforce standpoint, and to support the development of a data-driven strategy for meeting workforce needs (such as identifying skill gaps to be closed through training programs). This project will leverage an approach to estimating the similarity of requirements between different occupations, as well as other potential indicators of the feasibility of worker transitions from one occupation into another. These indicators will be tested against longitudinal evidence of realized occupational transitions and used to specify models that quantify the number of workers who may satisfy a minimum level of readiness for demand in any given occupation, and boundary estimates on the rate at which such workers might transition into the in-demand occupation. The outputs of this project will include an empirically validated user-tool that helps estimate potential stock and mobility of workers in every US metropolitan statistical area to meet demand for any occupation within the BLS SOC taxonomy, and the potential gaps between "candidate" occupations and the in-demand occupation. Underlying analytical models of the tool and its performance against historic mobility trends will be published. This tool will be applied to support a regional case analysis of workforce readiness for capacity-building in microelectronics in Florida and energy storage in New York.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.084

1

4900

4900

2435250

[{'FirstName': 'Ramayya', 'LastName': 'Krishnan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ramayya Krishnan', 'EmailAddress': 'RK2r@andrew.cmu.edu', 'NSF_ID': '000366661', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Christophe', 'LastName': 'Combemale', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christophe B Combemale', 'EmailAddress': 'ccombema@andrew.cmu.edu', 'NSF_ID': '000931639', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}

{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152133815', 'StreetAddress': '5000 FORBES AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}

{'Code': '226Y00', 'Text': 'Special Projects'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435250.xml'}

NSF-AoF: SOLID: System-wide Operation via Learning In-device Dissimilarities

NSF

01/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Phillip Regalia', 'PO_EMAI': 'pregalia@nsf.gov', 'PO_PHON': '7032922981'}

Cellular communication systems continue to incorporate new multiple-antenna technologies. In particular, third, fourth and fifth generation cellular systems saw advancements in the use of multiple antennas at the base-station infrastructure and multiple antennas in the devices. A main application of these antennas was to support multiple-input multiple-output (MIMO) communication, which is known to increase spectral efficiency and thus the data rates that can be achieved by devices in a given bandwidth. The numbers of antennas and the ways the antennas are used can vary across device models even from the same manufacturer. At the same time, the types of devices supported in cellular systems is growing beyond smartphones to include other highly mobile platforms like aerial vehicles, automobiles, and robots. The differences in the hardware between devices, coupled with the high device mobility, makes it challenging to configure the antennas to provide MIMO communication with the highest performance. This project develops machine learning-inspired solutions to empower devices to learn optimal configurations collaboratively. <br/><br/>System-wide Operation via Learning In-device Dissimilarities is a cooperation among experts in wireless communications at North Carolina State University (NC State) and Tampere University (TAU). The overall objective of the proposal is to employ machine-learning-assisted collaborative solutions for MIMO beam prediction and codebook optimization in a large-scale dynamic system. The key challenge of such networks is the extreme diversity of the devices’ hardware (e.g., antenna designs and configurations). The existing distributed ML approaches do not explicitly include this type of client heterogeneity and do not fully support the temporal and spatial heterogeneity of data, network resources, and deployments. The project team will develop a novel integrated-learning and wireless-networking framework, which will enable the design and optimization of advanced MIMO beam-management solutions specifically tailored to the highly diverse and dynamic system. This project will result in new algorithms for collaborative device-centric beam management for 5G+/pre-6G MIMO communications in non-stationary environments with highly mobile and heterogeneous agents. The specific technical contributions occur in several directions: (a) Distributed user-centric learning for optimizing codebook-based MIMO communications; (b) Novel representation of device heterogeneity in an ML-friendly way; and (c) Network-resource optimization to facilitate distributed learning. The immediate impact will be improved communication efficiency in 5G+/pre-6G networks. The longer-term impact will be the establishment of the core principles for designing fast and reliable methods of distributed ML training deployed over wireless systems with diverse hardware and resources.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/28/2024

06/28/2024

None

Grant

47.070

1

4900

4900

2435254

{'FirstName': 'Robert', 'LastName': 'Heath', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert W Heath', 'EmailAddress': 'rwheathjr@ucsd.edu', 'NSF_ID': '000257959', 'StartDate': '06/28/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}

{'Code': '779700', 'Text': 'Comm & Information Foundations'}

2022~486111

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435254.xml'}

NSF-IITP: START6G -- Sub-THz Augmented Routing and Transmission for 6G

NSF

01/01/2024

03/31/2025

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Jenshan Lin', 'PO_EMAI': 'jenlin@nsf.gov', 'PO_PHON': '7032927360'}

Terabit-per-second data rates will enable next-generation wireless cellular applications, including extended reality, holography, haptic feedback, and wireless cognition. These applications provide, in part, the means to create an immersive experience for work, education, and healthcare which helps to bridge the gap in experience between in-person interaction and video telephony. Achieving the high data rates, though, requires going to higher radio frequency bands than are currently used for cellular communications. In the last five years, cellular communication has embraced the lower millimeter wave spectrum, which refers to radio frequencies from about 25 GHz to 100 GHz. Indeed, millimeter wave communication has become one of the defining features of fifth generation cellular communication systems. Going to terabit-per-second data rates will require higher bandwidths that are available above 100 GHz, in what is known as the sub-THz band. This collaborative project establishes fundamentals that will help realize sub-THz communication and drive the future of wireless technology. It develops new hardware and algorithms that help to create the required high data rate communication links to serve the applications highlighted above. For example, it develops technology that helps sub-THz communication signals better go around obstacles, by instrumenting the environment with smart reflective surfaces and reconfigurable antenna arrays. The results of the project will contribute to the development of new wireless technologies that are beneficial for personal communication, safety applications and industrial deployments. Industry impact and technology transfer will occur through frequent communication with the partners of the sixth generation North Carolina program. The project will lead to more undergraduate and graduate students with expertise on new and important technologies for wireless communications.<br/><br/>Sub-THz Augmented Routing and Transmission for 6G is a collaboration among experts in wireless communications at North Carolina State University (NC State) and Yonsei University (YSU). It addresses the design of reflective surfaces and reconfigurable arrays for multiple-input multiple-output (MIMO) communication at sub-THz frequencies. It devises methods for configuring the beams formed or reflected from those arrays in a way that routes around obstacles. It creates algorithms that exploit new levels of reconfigurability in the arrays to obtain higher throughput and more robust communications. Finally, it results in the creation of joint real-time hardware (H/W) and software (S/W) testbeds for sub-THz communications. The uniqueness of this project lies in the multi-domain approach for improving sub-THz communications. The intellectual merit will occur in several directions. (a) Intelligent reflective surfaces constructed from state-of-the-art meta-materials / meta-devices. (b) Reconfigurable antenna arrays with adaptable structures that are mechanically and electrically controlled. (c) Directional-beam-based initial access and beam routing algorithms that leverage channel map information. (d) Models of reconfigurable antennas arrays and performance limits of those arrays. (e) Algorithms that leverage true time delays to reconfigure those arrays to support high bandwidths. (f) A suite of evaluation scenarios that test the developed hardware and algorithms. The immediate impact will be to identify the most relevant approaches for enabling large arrays for communication and reflective applications, as well as algorithms that leverage those arrays to enhance communication at sub-THz frequencies. The long-term impact will be in the development and realization of sub-THz communication as part of 6G wireless communications.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/17/2024

06/17/2024

None

Grant

47.041

1

4900

4900

2435261

{'FirstName': 'Robert', 'LastName': 'Heath', 'PI_MID_INIT': 'W', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Robert W Heath', 'EmailAddress': 'rwheathjr@ucsd.edu', 'NSF_ID': '000257959', 'StartDate': '06/17/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}

{'Code': '756400', 'Text': 'CCSS-Comms Circuits & Sens Sys'}

2022~229294

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435261.xml'}

Collaborative Research: Conference: GA6 Geosciences and Environmental Justice for Indigenous Communities

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}

{'SignBlockName': 'Nicole Gasparini', 'PO_EMAI': 'ngaspari@nsf.gov', 'PO_PHON': '7032920000'}

The 6th Geoscience Alliance (GA-6) conference builds on a successful series of national conferences aiming to broaden the participation of Native Americans in geoscience and environmental sciences. The first five Geoscience Alliance conferences brought together a total of more than 500 graduate, undergraduate, and K-12 students, educators, Elders, community members, and professionals representing 40 Tribes, Bands, and Native Villages. The GA-6 conference will take place in North Carolina and is expected to increase participation from the Southeast and Mid-Atlantic, regions that have been underrepresented at prior Geoscience Alliance conferences. The conference theme, Geoscience and Environmental Justice in Indigenous Communities, considers the distributions of environmental benefits and burdens along with the environmental policies, practices, and power dynamics that influence these distributions. Noting that Indigenous communities regularly shoulder disproportionately large environmental burdens from pollution, resource extraction, and climate change, conference participants will learn about, share, and discuss some of the ways that Indigenous and western knowledges can be used to address these problems and promote environmental justice. By increasing the involvement of Native American communities underrepresented in geoscience and environmental science, the conference will help enhance human capacity in these fields at a national level.<br/><br/>Despite growing recognition that Indigenous knowledge systems have much to offer the geoscience and environmental sciences, Indigenous peoples themselves are among the most underrepresented groups in careers and degree programs in these fields. This underrepresentation has implications for scientific research, science education, management, and other areas. The 6th Geoscience Alliance (GA-6) conference will help address this issue by building on a successful series of national conferences aimed at broadening the participation of Native Americans in geoscience and environmental sciences. The conference theme engages with Indigenous environmental justice, an area of academic research and a social movement that is both relevant to public policy and linked to scientific issues related to air and water quality, natural resource management, and climate change. In particular, the GA-6 conference will elevate Indigenous perspectives in environmental justice research, education, and engagement to spur ideas, dialog, and collaboration among participants and their networks. The three-day conference will include activities proven successful in previous Geoscience Alliance conferences: discussion circles, workshops, poster sessions, and field trips. The main objectives of the GA-6 conference are learning; networking and career progress; understanding; making it memorable; and growing the community. The conference will fulfill each of these objectives under the established and effective Geoscience Alliance principle that everyone teaches and everyone learns. The GA-6 conference will also serve to disseminate information to participants about opportunities such as Research Experience for Undergraduate programs, internships, and academic degree programs. A focus on networking at the conference will support all participants in developing a strong network of peers and collaborators.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/15/2024

08/15/2024

None

Grant

47.050

1

4900

4900

2435273

{'FirstName': 'Ryan', 'LastName': 'Emanuel', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ryan E Emanuel', 'EmailAddress': 'ree@duke.edu', 'NSF_ID': '000573967', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Duke University', 'CityName': 'DURHAM', 'ZipCode': '277054640', 'PhoneNumber': '9196843030', 'StreetAddress': '2200 W MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'TP7EK8DZV6N5', 'ORG_LGL_BUS_NAME': 'DUKE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Duke University', 'CityName': 'DURHAM', 'StateCode': 'NC', 'ZipCode': '277054640', 'StreetAddress': '2200 W MAIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}

{'Code': '157500', 'Text': 'EDUCATION AND HUMAN RESOURCES'}

2024~6983

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435273.xml'}

Collaborative Research: Conference: GA6 Geosciences and Environmental Justice for Indigenous Communities

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}

{'SignBlockName': 'Nicole Gasparini', 'PO_EMAI': 'ngaspari@nsf.gov', 'PO_PHON': '7032920000'}

The 6th Geoscience Alliance (GA-6) conference builds on a successful series of national conferences aiming to broaden the participation of Native Americans in geoscience and environmental sciences. The first five Geoscience Alliance conferences brought together a total of more than 500 graduate, undergraduate, and K-12 students, educators, Elders, community members, and professionals representing 40 Tribes, Bands, and Native Villages. The GA-6 conference will take place in North Carolina and is expected to increase participation from the Southeast and Mid-Atlantic, regions that have been underrepresented at prior Geoscience Alliance conferences. The conference theme, Geoscience and Environmental Justice in Indigenous Communities, considers the distributions of environmental benefits and burdens along with the environmental policies, practices, and power dynamics that influence these distributions. Noting that Indigenous communities regularly shoulder disproportionately large environmental burdens from pollution, resource extraction, and climate change, conference participants will learn about, share, and discuss some of the ways that Indigenous and western knowledges can be used to address these problems and promote environmental justice. By increasing the involvement of Native American communities underrepresented in geoscience and environmental science, the conference will help enhance human capacity in these fields at a national level.<br/><br/>Despite growing recognition that Indigenous knowledge systems have much to offer the geoscience and environmental sciences, Indigenous peoples themselves are among the most underrepresented groups in careers and degree programs in these fields. This underrepresentation has implications for scientific research, science education, management, and other areas. The 6th Geoscience Alliance (GA-6) conference will help address this issue by building on a successful series of national conferences aimed at broadening the participation of Native Americans in geoscience and environmental sciences. The conference theme engages with Indigenous environmental justice, an area of academic research and a social movement that is both relevant to public policy and linked to scientific issues related to air and water quality, natural resource management, and climate change. In particular, the GA-6 conference will elevate Indigenous perspectives in environmental justice research, education, and engagement to spur ideas, dialog, and collaboration among participants and their networks. The three-day conference will include activities proven successful in previous Geoscience Alliance conferences: discussion circles, workshops, poster sessions, and field trips. The main objectives of the GA-6 conference are learning; networking and career progress; understanding; making it memorable; and growing the community. The conference will fulfill each of these objectives under the established and effective Geoscience Alliance principle that everyone teaches and everyone learns. The GA-6 conference will also serve to disseminate information to participants about opportunities such as Research Experience for Undergraduate programs, internships, and academic degree programs. A focus on networking at the conference will support all participants in developing a strong network of peers and collaborators.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/15/2024

08/15/2024

None

Grant

47.050

1

4900

4900

2435274

{'FirstName': 'Jason', 'LastName': 'McLachlan', 'PI_MID_INIT': 'S', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jason S McLachlan', 'EmailAddress': 'jmclachl@nd.edu', 'NSF_ID': '000314164', 'StartDate': '08/15/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'ZipCode': '465565708', 'PhoneNumber': '5746317432', 'StreetAddress': '940 GRACE HALL', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'IN02', 'ORG_UEI_NUM': 'FPU6XGFXMBE9', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NOTRE DAME DU LAC', 'ORG_PRNT_UEI_NUM': 'FPU6XGFXMBE9'}

{'Name': 'University of Notre Dame', 'CityName': 'NOTRE DAME', 'StateCode': 'IN', 'ZipCode': '465566031', 'StreetAddress': '836 GRACE HALL', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'IN02'}

{'Code': '157500', 'Text': 'EDUCATION AND HUMAN RESOURCES'}

2024~93016

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435274.xml'}

CAREER: Fast optical voltage imaging for detailing bursts of neural activity

NSF

05/15/2024

03/31/2025

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Steve Zehnder', 'PO_EMAI': 'szehnder@nsf.gov', 'PO_PHON': '7032927014'}

The next step toward understanding the brain is to reveal how the different regions of the brain interact. This proposal creates an interdisciplinary set of protein and microscopy tools that optically captures and then interprets movies of the entire zebrafish brain. These large-scale recordings will help understand the relationship between different brain regions, especially during fast neural activity patterns associated with specific neural disorders. The technological and scientific products of this proposal will result in training materials that educate and inspire the next generation of neural engineers.<br/><br/>Neuroscience requires a mesoscopic study of the brain to define the functional relationships between different brain regions. This proposal creates a series of fluorescent genetically encoded voltage sensors, optical microscopes, and signal processing tools to optically extract the millisecond waveforms of targeted neural populations simultaneously over the entire zebrafish brain. These recordings will help characterize the cascade of fast, millisecond timescale bursts of neural activity expanding through multiple brain regions that underlie neural disorders. The broader impact goals of this proposal will fold these technological tools into educational and research training materials targeted to a diverse array of students in the STEM pipeline.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/30/2024

07/30/2024

None

Grant

47.041

1

4900

4900

2435283

{'FirstName': 'Yiyang', 'LastName': 'Gong', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Yiyang Gong', 'EmailAddress': 'yiyang-gong@ouhsc.edu', 'NSF_ID': '000688484', 'StartDate': '07/30/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Oklahoma Health Sciences Center', 'CityName': 'OKLAHOMA CITY', 'ZipCode': '731043609', 'PhoneNumber': '4052712090', 'StreetAddress': '865 RESEARCH PKWY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oklahoma', 'StateCode': 'OK', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'OK05', 'ORG_UEI_NUM': 'GY8NMUZQXVS7', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF OKLAHOMA', 'ORG_PRNT_UEI_NUM': 'GY8NMUZQXVS7'}

{'Name': 'University of Oklahoma Health Sciences Center', 'CityName': 'OKLAHOMA CITY', 'StateCode': 'OK', 'ZipCode': '731043609', 'StreetAddress': '865 RESEARCH PKWY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oklahoma', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'OK05'}

{'Code': '723600', 'Text': 'BioP-Biophotonics'}

2019~434716

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435283.xml'}

IUCRC Planning Grant Massachusetts Institute of Technology: Center for Climate Risks Applications (CCRA)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': 'bransom@nsf.gov', 'PO_PHON': '7032927792'}

As human-emitted greenhouse gas pollution warms the planet and changes the dynamics of the climate system, losses due to weather extremes and their impacts on human life and property has become a significant and costly challenge. Reliance on historical records with outdated climate states, coarse model resolution, and incongruency between the spatiotemporal scale of impacts exacerbates the problem and presents serious difficulties for the insurance and finance sectors that rely on accurate assessment of natural perils and the corresponding uncertainties around their frequency, intensity, and duration. This knowledge is required to cover climate disaster related losses that, annually, reach well into tens to hundreds of billions of dollars. To address this challenge, three institutions: George Mason University, the Massachusetts Institute of Technology, and the City University of New York have come together to plan an industry-university cooperative research center that addresses the critical, high priority needs of the insurance and finance sectors, both of which are wrestling with uncertainties in assessing risks and damages due to climate-related disasters. Center research thrusts include: (1) improving climate predictions at spatiotemporal scales needed by the insurance and finance industries; (2) modeling the catastrophic impacts of natural perils to critical infrastructure systems; and (3) quantifying how the local environment modifies the frequency, intensity, and impact of weather-related natural perils on people and property. Broader impacts of the Center would include increased national economic stability by providing better and more reliable tools for assessing climate risk; training the next generation of climate science, engineering, and policy professionals able to tackle the challenges that a changing climate poses to the nation; and broadening the diversity of underrepresented groups in climate disaster modeling field.<br/><br/>Research conducted by the Center for Climate Risk Applications, now in the planning phase, will focus on addressing existing gaps on the impact of climate change on a range of natural perils by analyzing state-of-the-art climate model ensembles, improving existing models, and advancing the science of integration between climate modeling and asset-scale risks. Research will analyze and improve the output of climate models at the actionable spatial and temporal scales required by the insurance and finance sectors of the economy. The Center will also develop new methods for downscaling hazard information to asset-scale granularity, while quantifying uncertainties of year-to-decadal climate predictions. Additional work will address the sensitivity of interconnected infrastructure systems to a changing landscape of natural perils and the potential for disruption of critical services and supply/value chains. Natural disasters impact people, not just infrastructure; thus, the Center, presently in the planning stage will also focus on how public policy and regulation impacts the insurance of properties, as well as how existing frameworks for decision-making around these perils inform resilience efforts in the private and public sectors. The Center's education and outreach activities will help enable and maintain healthy insurance and reinsurance markets to promote economic stability and growth in the face of severe threats from climate change to life and property. It will also develop a diverse, knowledgeable, and capable workforce necessary to quantify risks of climate change for those owning assets that need protection as well as the need to improve their ability to understand and predict risks and create policies, standards, and incentives that reduce the risks of loss due to climate change. The role of the Massachusetts Institute of Technology's role will be the contribution of multi-sector and cascading disaster dynamics, policy, and climate science.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/22/2024

08/22/2024

None

Grant

47.050

1

4900

4900

2435284

{'FirstName': 'Courtney', 'LastName': 'Schlosser', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Courtney A Schlosser', 'EmailAddress': 'casch@mit.edu', 'NSF_ID': '000109943', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'ZipCode': '021394301', 'PhoneNumber': '6172531000', 'StreetAddress': '77 MASSACHUSETTS AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'E2NYLCDML6V1', 'ORG_LGL_BUS_NAME': 'MASSACHUSETTS INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': 'E2NYLCDML6V1'}

{'Name': 'Massachusetts Institute of Technology', 'CityName': 'CAMBRIDGE', 'StateCode': 'MA', 'ZipCode': '021394301', 'StreetAddress': '77 MASSACHUSETTS AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': 'Y17300', 'Text': None}

2024~19999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435284.xml'}

Conference: INCLUDES FY24: Workshop: Faculty Development Four Corners STEM Alliance (FCSA) Workshop to Enhance Competitiveness in Proposal Preparation, August 22-24, 2024

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '11060000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'EES', 'LongName': 'Div. of Equity for Excellence in STEM'}}

{'SignBlockName': "Sally O'Connor", 'PO_EMAI': 'soconnor@nsf.gov', 'PO_PHON': '7032924552'}

The University of Wyoming will conduct a three-day hybrid workshop designed to empower faculty members and administrators from tribal colleges, community colleges, and predominantly undergraduate institutions across the Mountain States—Colorado, Montana, Utah, and Wyoming. This innovative workshop will host 30 participants, providing them with a unique platform to interact directly with NSF program staff and peers. The goal is to foster an environment where participants are welcomed and trusted, where they can directly engage with NSF program staff and peers to master the art of grant proposal writing. This effort is not just about securing funds; it’s about advancing scientific discovery, enhancing educational opportunities, and promoting inclusive excellence.<br/><br/>Participants will engage in an immersive experience that focuses on the development of effective grant proposals, targeting both federal funding and private sector grants. The workshop is structured to enhance understanding of the grant application process, offering hands-on guidance in creating compelling narratives and robust budget plans. The workshop is designed to offer comprehensive training that delves into the development of grant proposal writing, ensuring participants are well-versed in the key elements that make a successful application. It aims to guide attendees in crafting proposals that not only meet but resonate with the National Science Foundation’s funding priorities, enhancing the likelihood of securing support. Key features of the workshop include: 1) Interactive Sessions with NSF program staff to demystify the grant application process; 2) Practical tools such as budget management templates to aid in the development of NSF grant applications; 3) Collaborative opportunities for participants to form networks, fostering long-term partnerships and knowledge exchange; and 4) Focused Breakout Groups to address critical topics like responsible research conduct, mentoring, diversity, and scientific communication. By the end of the workshop, attendees will not only gain valuable insights into grant writing but also leave with a tangible product to enhance their proposal submissions. <br/><br/>This workshop is supported by NSF Directorate for Biological Sciences (BIO), STEM Education (EDU) and Computer and Information Science and Engineering (CISE), and the Office of Integrative Affairs (OIA).<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/11/2024

07/11/2024

None

Grant

47.070, 47.074, 47.076

1

4900

4900

2435285

{'FirstName': 'Camellia', 'LastName': 'Okpodu', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Camellia M Okpodu', 'EmailAddress': 'cokpodu@uwyo.edu', 'NSF_ID': '000251604', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'ZipCode': '820712000', 'PhoneNumber': '3077665320', 'StreetAddress': '1000 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wyoming', 'StateCode': 'WY', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'WY00', 'ORG_UEI_NUM': 'FDR5YF2K32X5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WYOMING', 'ORG_PRNT_UEI_NUM': 'FDR5YF2K32X5'}

{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'StateCode': 'WY', 'ZipCode': '820712000', 'StreetAddress': '1000 E UNIVERSITY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wyoming', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'WY00'}

[{'Code': '032Y00', 'Text': 'Eddie Bernice Johnson INCLUDES'}, {'Code': '113900', 'Text': 'RSCH EXPER FOR UNDERGRAD SITES'}, {'Code': '173Y00', 'Text': 'CISE MSI Research Expansion'}]

2024~98642

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435285.xml'}

Conference: Quantum+Chips Summer School at University of Minnesota 2024

NSF

08/01/2024

01/31/2026

{'Value': 'Standard Grant'}

{'Code': '07010000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'ECCS', 'LongName': 'Div Of Electrical, Commun & Cyber Sys'}}

{'SignBlockName': 'Usha Varshney', 'PO_EMAI': 'uvarshne@nsf.gov', 'PO_PHON': '7032925385'}

The rapid expansion of workforce development for future computing technologies is needed to meet the demands of the semiconductor industry in creating next-generation computing and memory devices. Despite its crucial role in contemporary technology, the semiconductor industry lacks the visibility of more glamorous sectors such as internet and software technologies. The semiconductor workforce requires a unique and complex set of skills across diverse fields, which typically necessitates specialized training through advanced undergraduate and post-graduate programs. This team is dedicated to educating the next generation of skilled technical professionals, focusing on materials and device co-design approaches through innovative immersive experiences. Summer school programs at the college level can effectively raise awareness about workforce needs in the country, the exciting deep technologies, vast career opportunities, networking prospects, and the enjoyable science involved in this work. This summer school, with its multi-pronged, holistic approach that incorporates academic and industry participation, aims to provide students with training and experience in "Quantum + Chips." Additionally, the goal is to inspire students by demonstrating the fun aspects of the physics underlying these technologies.<br/><br/>The planned summer school will be held at the University of Minnesota from July 29th to August 9th, 2024. This 2-week immersive summer experience is designed for undergraduate students, from freshmen to seniors, to expose them to a wide range of computing technologies and paradigms. The first week includes curated lectures focusing on physics and computing fundamentals, computer labs, experimental labs, and demonstrations. Topics covered include fundamental concepts of quantum mechanics, semiconductor physics, carrier statistics, quantum transport, transistors, spintronics, and quantum computing, among others. The second week features company visits and talks by industry and academic experts on the latest advancements in computing devices and technologies. Technical talks will cover topics such as transistors, optical computing, spintronics, Ising computing, and quantum computing. Speakers from participating semiconductor and quantum technology companies will provide technical and career talks, along with company tours. Student lodging will be provided for the summer school participants. Surveys indicate that students enjoy the dormitory experience and the networking opportunities with their peers in other institutions.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2435298

[{'FirstName': 'Jian-Ping', 'LastName': 'Wang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jian-Ping Wang', 'EmailAddress': 'jpwang@umn.edu', 'NSF_ID': '000385176', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Tony', 'LastName': 'Low', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Tony Low', 'EmailAddress': 'tonyaslow@gmail.com', 'NSF_ID': '000679004', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'ZipCode': '554552009', 'PhoneNumber': '6126245599', 'StreetAddress': '200 OAK ST SE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Minnesota', 'StateCode': 'MN', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'MN05', 'ORG_UEI_NUM': 'KABJZBBJ4B54', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF MINNESOTA', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Minnesota-Twin Cities', 'CityName': 'MINNEAPOLIS', 'StateCode': 'MN', 'ZipCode': '554550169', 'StreetAddress': '200 Union ST SE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Minnesota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'MN05'}

{'Code': '151700', 'Text': 'EPMD-ElectrnPhoton&MagnDevices'}

2024~30000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435298.xml'}

Adaptive Dependent Data Models via Graph-Informed Shrinkage and Sparsity

NSF

07/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '04050000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'SES', 'LongName': 'Divn Of Social and Economic Sciences'}}

{'SignBlockName': 'Cheryl Eavey', 'PO_EMAI': 'ceavey@nsf.gov', 'PO_PHON': '7032927269'}

This research project will advance statistical modeling and computing strategies for dependent data. Dependent data are widespread and important. Many socioeconomic, cultural, and political data are measured on spatial areal units, most economic data are time-ordered and co-dependent, and modern monitoring systems record social, environmental, and economic exposure data at near-continuous resolutions. However, this growing abundance of dependent data has outpaced the development of statistical methods and algorithms for such data. The project will develop new statistical tools that will allow researchers to extract reliable information and make decisions from such dependent data. The methods to be developed will be motivated by specific, timely, and important problems in the following areas: local elections and redistricting; inflation modeling and forecasting; spatial pattern extraction for economic, health, and urban data; and modeling of monitoring and exposure data. The project will provide training and mentoring for undergraduate and graduate students, develop publicly available software and visualization tools, and showcase local, state, and federal government data.<br/><br/>This research project will develop new statistical tools to adequately capture a broad array of data dependencies, provide computational scalability for massive datasets, and leverage the dependence structures for more adaptive and localized estimation, uncertainty quantification, and imputation of missing data. Unmodeled dependence renders inferences suboptimal or invalid, resulting in underpowered analyses and erroneous conclusions. In addition, dependent data are often high-dimensional with substantial missingness, leading to significant computational and statistical challenges. Within a Bayesian framework, the project will simultaneously integrate the dependence in (i) the model for the signal to provide smoothness and regularization, (ii) the accompanying shrinkage or sparsity prior for enhanced local adaptivity, and (iii) the computational and numerical strategies for scalable posterior inference. Dependence will be encoded as a graph that links together observational units, such as consecutive observations for time-ordered or functional data, adjacent pixels for image or lattice data, and neighboring areal units for spatial data, among many other examples. This graph-based formulation will lay the foundation to unify and advance a broad collection of models, shrinkage and sparsity priors, and inference algorithms for dependent data. The tools to be developed will be customized for a variety of settings, including trend estimation and imputation, shrinkage or sparsity priors, graph-informed regression analysis, factor models, and discrete data, among others.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.075

1

4900

4900

2435310

{'FirstName': 'Daniel', 'LastName': 'Kowal', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Daniel Kowal', 'EmailAddress': 'daniel.kowal@rice.edu', 'NSF_ID': '000762747', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Cornell University', 'CityName': 'ITHACA', 'ZipCode': '148502820', 'PhoneNumber': '6072555014', 'StreetAddress': '341 PINE TREE RD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'G56PUALJ3KT5', 'ORG_LGL_BUS_NAME': 'CORNELL UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Cornell University', 'CityName': 'ITHACA', 'StateCode': 'NY', 'ZipCode': '148502820', 'StreetAddress': '341 PINE TREE RD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}

{'Code': '133300', 'Text': 'Methodology, Measuremt & Stats'}

2022~226874

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435310.xml'}

Conference: CIRC Principal Investigators Meeting

NSF

11/01/2024

10/31/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Deepankar Medhi', 'PO_EMAI': 'dmedhi@nsf.gov', 'PO_PHON': '7032922935'}

The purpose of this project is to organize and host the 2025 Principal Investigators Meeting for National Science Foundation (NSF) Community Infrastructure for Research in CISE (CIRC) and also for Major Research Instrumentation (MRI) awardees in NSF's Computer & Network Systems Division (CNS) in Raleigh, North Carolina. The meeting is expected to be held for two days starting March 10th, 2025. It will involve participants, including Principal Investigators (PIs), NSF Program Directors, and the organizing team. <br/><br/>The 2-day program will include a keynote, presentations by the PIs of featured projects, panel discussions, poster presentation, a reception, and “office hours” with Program Directors. The meeting will be where PIs, Program Directors, and others meet to present and exchange information about projects supported by the NSF’s CIRC and CNS's MRI Programs, discuss research infrastructure opportunities and challenges, and explore new ideas and partnerships for future work. It is also an opportunity for the academic community to interact with government agencies interested in research infrastructure developments and advancements. The Meeting series has played a major role in growing the community across a broad range of sectors and technologies, as well as in performing outreach to parties who have an interest in learning about the program and participating as future proposers, transition partners, or sponsors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/31/2024

07/31/2024

None

Grant

47.070

1

4900

4900

2435313

[{'FirstName': 'Magreth', 'LastName': 'Mushi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Magreth Mushi', 'EmailAddress': 'mjmushi@ncsu.edu', 'NSF_ID': '000871534', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Ozgur', 'LastName': 'Ozdemir', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ozgur Ozdemir', 'EmailAddress': 'oozdemi@ncsu.edu', 'NSF_ID': '000768434', 'StartDate': '07/31/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'North Carolina State University', 'CityName': 'RALEIGH', 'ZipCode': '276950001', 'PhoneNumber': '9195152444', 'StreetAddress': '2601 WOLF VILLAGE WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_ORG': 'NC02', 'ORG_UEI_NUM': 'U3NVH931QJJ3', 'ORG_LGL_BUS_NAME': 'NORTH CAROLINA STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NVH931QJJ3'}

{'Name': 'North Carolina State University', 'CityName': 'RALEIGH', 'StateCode': 'NC', 'ZipCode': '276950001', 'StreetAddress': '2601 WOLF VILLAGE WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '02', 'CONGRESS_DISTRICT_PERF': 'NC02'}

{'Code': '735900', 'Text': 'CCRI-CISE Cmnty Rsrch Infrstrc'}

2024~99212

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435313.xml'}

CAREER: How Memory Contributes to Goal-Directed Attention

NSF

07/01/2024

02/28/2026

{'Value': 'Continuing Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Dwight Kravitz', 'PO_EMAI': 'dkravitz@nsf.gov', 'PO_PHON': '7032924502'}

Memory is a critical aspect of many of our behaviors. We use memory to find our way around, to detect a familiar face in a crowd, and to keep track of our ideas as we speak and write. One powerful way that memory can affect so many of our behaviors is by helping to guide what we pay attention to. For example, in a messy kitchen, you can use your memory for where mugs are typically stored in order to find one. Therefore, although memory is often studied for its own sake - for example, to understand how we are able to reminisce about the past, or how that process can go wrong - it is also critically important to understand how we can use memory in the service of guiding our attention and actions. The goal of this project is to understand how the functioning of the human brain enables us to use memories of the past to direct our attention, and the consequences that has for how quickly and accurately we can accomplish tasks. In doing so, this work will highlight the critical importance of memory for moment-to-moment attention. This will fill an important gap in scientific research, which often studies attention and memory in isolation. It will highlight the fundamentally interactive nature of our past and current experiences, with implications for how learning and remembering in educational settings can affect attention and future learning in a feedback loop.<br/><br/>This project therefore seeks to determine the neural mechanisms by which memories guide attention, focusing on the memories stored in a key brain region that is critical for building new memories and retrieving old ones: the hippocampus. This will be accomplished in two Aims, which use multiple methods: functional magnetic resonance imaging, studies of patients with brain lesions, eye tracking, and measures of behavioral accuracy and response times. In Aim 1, the project will determine the neural circuits for memory-guided attention and their relationship to behavior. The main hypothesis is that a brain network including the hippocampus and prefrontal and visual cortices allows us to use memory to update attentional goals and anticipate task-relevant information before it appears. This hypothesis will be tested using a novel approach of characterizing interactions between brain regions (representational connectivity), which<br/>enables investigation of synchrony in information content between regions. In Aim 2, this project will establish how memory and attention jointly guide visual exploration. The main hypothesis is that hippocampal memory retrieval of prior attentional goals will influence visual exploration, attention, and memory in novel situations. This work will have innovative implications for education, e.g., the use of eye tracking to identify if students are remembering and attending to relevant information, even if they cannot<br/>verbally describe it. Together, these two Aims will start to uncover the powerful way that memories can influence our in-the-moment attentional behaviors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.075

1

4900

4900

2435322

{'FirstName': 'Mariam', 'LastName': 'Aly', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mariam Aly', 'EmailAddress': 'mariamaly@berkeley.edu', 'NSF_ID': '000772064', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'ZipCode': '947101749', 'PhoneNumber': '5106433891', 'StreetAddress': '1608 4TH ST STE 201', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'CA12', 'ORG_UEI_NUM': 'GS3YEVSS12N6', 'ORG_LGL_BUS_NAME': 'REGENTS OF THE UNIVERSITY OF CALIFORNIA, THE', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Berkeley', 'CityName': 'BERKELEY', 'StateCode': 'CA', 'ZipCode': '947101749', 'StreetAddress': '1608 4TH ST STE 201', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'CA12'}

{'Code': '169900', 'Text': 'Cognitive Neuroscience'}

['2022~100946', '2023~82465']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435322.xml'}

CAREER: Beyond Approximate Computing: Enabling Full-System Energy-Quality Scalability in Embedded Systems

NSF

01/01/2024

05/31/2025

{'Value': 'Continuing Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Marilyn McClure', 'PO_EMAI': 'mmcclure@nsf.gov', 'PO_PHON': '7032925197'}

Energy efficiency is a daunting challenge in embedded systems that run on limited energy budgets. Better performance, longer battery life, and smaller environmental footprints - improving energy efficiency will be the key enabler of applications and services that have not been possible in the past. Approximate computing has recently emerged as a promising approach to the energy-efficient computing of intrinsically error-tolerant applications like image processing, where small deviations from the exact results in the underlying computations do not substantially degrade the resulting application-level quality. For such applications, approximate computing can produce "just good enough" results to save energy at the cost of only minor or no quality loss.<br/><br/>This project will develop design methodologies for taking advantage of approximate computing in embedded systems, where the contribution of non-computing subsystems (e.g., sensors, actuators, user interfaces, and network interfaces) to energy consumption is at least as significant as that of computing subsystems (e.g., microcontrollers and memory). In embedded systems, both computing and non-computing subsystems must be holistically considered to take full advantage of approximate computing and accomplish full-system energy quality and scalability. The project scope includes characterization, optimization, and design toolchain development, with the focus on embedded systems design.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/02/2024

07/02/2024

None

Grant

47.070

1

4900

4900

2435327

{'FirstName': 'Younghyun', 'LastName': 'Kim', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Younghyun Kim', 'EmailAddress': 'younghyun@purdue.edu', 'NSF_ID': '000737914', 'StartDate': '07/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'ZipCode': '479061332', 'PhoneNumber': '7654941055', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Indiana', 'StateCode': 'IN', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'IN04', 'ORG_UEI_NUM': 'YRXVL4JYCEF5', 'ORG_LGL_BUS_NAME': 'PURDUE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'YRXVL4JYCEF5'}

{'Name': 'Purdue University', 'CityName': 'WEST LAFAYETTE', 'StateCode': 'IN', 'ZipCode': '479061332', 'StreetAddress': '2550 NORTHWESTERN AVE # 1100', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Indiana', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'IN04'}

{'Code': '735400', 'Text': 'CSR-Computer Systems Research'}

['2022~76482', '2023~110371']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435327.xml'}

CAREER: Stimuli-responsive biomaterials for wound healing and drug delivery

NSF

07/01/2024

12/31/2027

{'Value': 'Continuing Grant'}

{'Code': '03070000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMR', 'LongName': 'Division Of Materials Research'}}

{'SignBlockName': 'Nitsa Rosenzweig', 'PO_EMAI': 'nirosenz@nsf.gov', 'PO_PHON': '7032927256'}

Non-technical abstract<br/><br/>Wound healing and arthritis treatment are two areas that people care about. New classes of “smart” hydrogels that respond to environment and change their stiffness will be developed for removable wound dressings and arthritis treatment. This work will improve healing outcome for millions of patients each year. In addition to practical applications, these materials will provide tools and methods that could be used by everyone to rationally design hydrogel materials and will contribute to development of the wider fields of dynamic nanomaterials, drug delivery and biosensing. The educational component integrates research efforts and several education programs in biomaterials by 1) developing a research training program for high school students from Syracuse City School District (SCSD); 2) providing research training for undergraduate students that participate in Reserve Officer Training Corps (ROTC) at Syracuse University and 3) designing an outreach model of biomaterials for the Milton J. Rubinstein Museum of Science and Technology (MOST) in Syracuse. Through these multi-prong outreach programs, students across different age groups will be inclusively engaged with a particular emphasis on training women, underrepresented minorities, and refugees. Educational programs will not only provide a training ground for future biochemists but will also generate valuable results to advance the research field. <br/><br/>Technical abstract<br/><br/>The goal of this proposal is to design peptide-based, smart, stimuli-responsive biocompatible antimicrobial materials that change their stiffness in response to changes in redox state and pH. Synergistic combination of multiple properties is critically important because self-healing is essential for delivery of the hydrogel via a syringe, antimicrobial properties and cytocompatibility are critical for practical applications, and redox switching allows the removal of the gel upon addition of a mild reductant or drug release in response to reactive oxygen species (ROS). Toward this goal, three classes of stimuli-responsive materials with self-healing properties will be designed: 1) redox-sensitive peptide hydrogels; 2) pH-responsive hydrogel to deliver fibroblast cells into wound bed; 3) hydrogels that respond to both changes in pH and ROS. This work will generate hydrogel materials for wound care and arthritis treatment and will provide tools and methods for rational design of functional materials.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/27/2024

06/27/2024

None

Grant

47.049

1

4900

4900

2435368

{'FirstName': 'Olga', 'LastName': 'Makhlynets', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Olga Makhlynets', 'EmailAddress': 'ovmakhly@syr.edu', 'NSF_ID': '000768131', 'StartDate': '06/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Baylor University', 'CityName': 'WACO', 'ZipCode': '767061003', 'PhoneNumber': '2547103817', 'StreetAddress': '700 S UNIVERSITY PARKS DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '17', 'CONGRESS_DISTRICT_ORG': 'TX17', 'ORG_UEI_NUM': 'C6T9BYG5EYX5', 'ORG_LGL_BUS_NAME': 'BAYLOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Baylor University', 'CityName': 'WACO', 'StateCode': 'TX', 'ZipCode': '767061003', 'StreetAddress': '700 S UNIVERSITY PARKS DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '17', 'CONGRESS_DISTRICT_PERF': 'TX17'}

{'Code': '762300', 'Text': 'BIOMATERIALS PROGRAM'}

['2023~29314', '2024~116284']

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435368.xml'}

NSF-SNSF: Molecular Mechanism of a Life-History Tradeoff between Growth and Survival

NSF

09/01/2024

08/31/2027

{'Value': 'Continuing Grant'}

{'Code': '08090000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'IOS', 'LongName': 'Division Of Integrative Organismal Systems'}}

{'SignBlockName': 'Anna Allen', 'PO_EMAI': 'akallen@nsf.gov', 'PO_PHON': '7032928011'}

Evolutionary adaptation often involves “fitness tradeoffs” where optimization of one trait comes at the expense of another. For example, a tradeoff between the ability to survive starvation and growth rate upon recovery has been documented in a variety of organisms. However, the molecular mechanisms that underly such tradeoffs are hardly understood despite being fundamental to evolutionary adaption. The roundworm C. elegans is a powerful model system that experiences feast or famine in the wild, and these worms display a tradeoff between starvation survival and recovery rate. The research team has developed an innovative approach using DNA sequencing of mixed populations to measure the fitness of competing strains during starvation and recovery. They have also developed imaging tools to precisely measure biochemical properties of these worms during starvation and recovery. These approaches will enable them to identify strains that are most fit in different evolutionary scenarios and to characterize the molecular mechanisms that support fitness. Each member of the team will engage in outreach. Dr. Baugh will host high school students from underrepresented backgrounds in his lab during the summer as part of Duke’s Cell Biology Academy (CeBA), and he will visit Dr. Towbin to learn innovative pedagogical methods from the Pestallozzi School Camps (PSCs). The PSCs have a similar mission to the CeBA but have been in operation much longer, and cross-participation will foster the exchange of ideas and approaches. This work will address a fundamental problem in evolutionary biology, advance state-of-the-art approaches, and engage students in research.<br/><br/>Evolutionary adaptation to different niches is shaped by phenotypic tradeoffs between life-history traits. Yet the proximal molecular mechanisms of life-history tradeoffs are unknown. The team proposes using the nematode C. elegans to address this knowledge gap and determine the molecular basis of a life-history tradeoff between growth and survival. C. elegans is a powerful animal model to address the molecular mechanisms of trait evolution given its genetic tractability, well-characterized development, short lifecycle, and the availability of hundreds of genetically diverse wild strains with sequenced genomes. The central hypothesis of this proposal is that the frequency and duration of larval starvation in a niche shapes the evolution of a phenotypic tradeoff between starvation survival and recovery speed, and that molecular rates of autophagy/ribophagy impact the balance between the two. This hypothesis will be tested using experimental evolution, genetics, proteomics, quantitative live imaging, and mathematical modeling. The goals of this proposal are to identify wild strains with different life-history strategies in response to starvation, evaluate the mechanistic contribution of autophagy and ribophagy rates to natural variation in starvation survival and recovery speed, and to identify genetic variants that influence the tradeoff between survival and recovery and the molecular mechanism affected. Accomplishment of these goals will be impactful by illustrating the importance of a particular tradeoff to evolutionary adaptation to different niches and by linking adaptation to a particular, conserved molecular mechanism. <br/><br/>This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

06/27/2024

06/27/2024

None

Grant

47.074

1

4900

4900

2435369

{'FirstName': 'Larry', 'LastName': 'Baugh', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Larry R Baugh', 'EmailAddress': 'ryan.baugh@duke.edu', 'NSF_ID': '000555348', 'StartDate': '06/27/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Duke University', 'CityName': 'DURHAM', 'ZipCode': '277054640', 'PhoneNumber': '9196843030', 'StreetAddress': '2200 W MAIN ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Carolina', 'StateCode': 'NC', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'NC04', 'ORG_UEI_NUM': 'TP7EK8DZV6N5', 'ORG_LGL_BUS_NAME': 'DUKE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Duke University', 'CityName': 'DURHAM', 'StateCode': 'NC', 'ZipCode': '277054640', 'StreetAddress': '2200 W MAIN ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Carolina', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'NC04'}

{'Code': '111900', 'Text': 'Animal Developmental Mechanism'}

2024~299999

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435369.xml'}

IUCRC Planning Grant University of North Dakota: Center for Infrastructure Security in the Era of AI (ISEAI)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Mohan Kumar', 'PO_EMAI': 'mokumar@nsf.gov', 'PO_PHON': '7032927408'}

This Industry University Cooperative Research Center (IUCRC) award funds the planning phase of the University of North Dakota (UND) in their activities to join the proposed Center for Infrastructure Security in the Era of AI (ISEAI). George Mason University (GMU) is the lead site of the Phase I proposal for creating ISEAI. ISEAI aims to address the urgent need for robust protection against cyber threats in vital sectors like financial services, energy, and healthcare. By focusing on these high-risk areas, the project supports national security and economic stability. After successful completion of the planning phase, the (UND) proposers will be eligible to submit a site addition proposal to join an existing IUCRC. <br/><br/>The grant aims to initiate collaboration between academic researchers and industry partners to explore and address current and future cyber threats to critical infrastructure. It will utilize AI to enhance resilience against both traditional and AI-enabled attacks. UND will collaborate with industry and government partners across the North Central region, including North Dakota, South Dakota, Minnesota, and surrounding areas, to develop innovative solutions for securing diverse infrastructure systems—from transportation to energy distribution.<br/><br/>This initiative has the potential to make an impact by translating research findings into practical applications that improve infrastructure security. UND’s expertise in cybersecurity, energy research, and unmanned aerial systems (UAS) will drive advancements in technology and foster a collaborative environment among researchers, industry, and government. The grant will facilitate technology transfer, promote economic growth, and contribute significantly to national security and resilience. The project will positively influence workforce development by involving students at all educational levels.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/16/2024

08/16/2024

None

Grant

47.070

1

4900

4900

2435371

[{'FirstName': 'Prakash', 'LastName': 'Ranganathan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Prakash Ranganathan', 'EmailAddress': 'prakash.ranganathan@engr.und.edu', 'NSF_ID': '000620646', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Diego', 'LastName': 'Fregolent Mendes de Oliv', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Diego Fregolent Mendes de Oliv', 'EmailAddress': 'diego.fregolent@und.edu', 'NSF_ID': '000876339', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Jielun', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Jielun Zhang', 'EmailAddress': 'jielun.zhang@und.edu', 'NSF_ID': '000948691', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Sicong', 'LastName': 'Shao', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Sicong Shao', 'EmailAddress': 'sicong.shao@und.edu', 'NSF_ID': '000952151', 'StartDate': '08/16/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of North Dakota Main Campus', 'CityName': 'GRAND FORKS', 'ZipCode': '582028371', 'PhoneNumber': '7017774151', 'StreetAddress': '264 CENTENNIAL DR STOP 8371', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'North Dakota', 'StateCode': 'ND', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'ND00', 'ORG_UEI_NUM': 'RSWNKK6J8CF3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF NORTH DAKOTA', 'ORG_PRNT_UEI_NUM': 'L4NWBKHV1J23'}

{'Name': 'University of North Dakota Main Campus', 'CityName': 'GRAND FORKS', 'StateCode': 'ND', 'ZipCode': '582028371', 'StreetAddress': '264 CENTENNIAL DR STOP 8371', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'North Dakota', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'ND00'}

[{'Code': '171400', 'Text': 'Special Projects - CNS'}, {'Code': '576100', 'Text': 'IUCRC-Indust-Univ Coop Res Ctr'}]

2024~18231

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435371.xml'}

EAGER: Ultrafast Laser-Based Synthesis of Nanoparticle-Doped Two-Dimensional Material Inks for Printed Electronics

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '07030000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CMMI', 'LongName': 'Div Of Civil, Mechanical, & Manufact Inn'}}

{'SignBlockName': 'Khershed Cooper', 'PO_EMAI': 'khcooper@nsf.gov', 'PO_PHON': '7032927017'}

This EArly-concept Grants for Exploratory Research (EAGER) project focuses on gaining a fundamental understanding of the basic research for creating doped two-dimensional (2D) material inks for printed electronics. Two-dimensional (2D) materials are an upcoming class of promising materials with tunable properties for use in next-generation flexible electronics. Nanoparticle-doped 2D materials can generate low-power, high-speed flexible electronic devices as doping controls the tuning of electrical, magnetic, and mechanical properties. Current leading techniques for generating doped 2D materials, such as atomic layer deposition and chemical vapor deposition are incompatible with printed electronics since they cannot provide inks that can be used directly in printers. This research studies ultrafast laser ablation synthesis in solution to create nanoparticle-doped 2D material inks. The project aims to build new knowledge in understanding the underlying mechanisms that control the synthesis of doped 2D materials using LASiS and manufacturing these in large volumes for practical use. In collaboration with Louis Stokes Alliance for Minority Participation (LSAMP), this project contributes to the education and training of graduate and undergraduate students from underrepresented minority communities in ultrafast laser science and ink synthesis. The printed devices are used in educational activities to introduce K-12 students to STEM fields.<br/><br/>This research obtains a fundamental understanding of laser-based synthesis of nanoparticle-doped 2D material inks and creates a manufacturing technique to generate large volumes of the inks for printed electronics. Utilizing femtosecond laser ablation synthesis in solution (LASiS), the 2D materials are generated from bulk. This is followed by intercalation doping, wherein nanoparticles are inserted in the Van der Waals layers of the 2D materials thus modifying their electrical, magnetic, and mechanical properties. This research focuses on the generation and intercalation of TiO2, gold, and platinum nanoparticles between graphene and MoS2. The effects of laser parameters, such as repetition rate, energy and focal spot size on the chemical composition, size, and generation rate of the doped 2D material inks are investigated. The knowledge gained provides insights into the fundamental mechanisms for the creation and intercalation doping of 2D materials. The project further investigates techniques to increase the production volume of ink through variation of sample stage speed, and use of multiple laser beams. The inks generated are printed using aerosol-jet printing and the quality of the thin films are analyzed by XRD, UV-VIS Raman, and I-V curves.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/07/2024

08/07/2024

None

Grant

47.041

1

4900

4900

2435383

{'FirstName': 'Nirmala', 'LastName': 'Kandadai', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nirmala Kandadai', 'EmailAddress': 'kandadan@oregonstate.edu', 'NSF_ID': '000769538', 'StartDate': '08/07/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'ZipCode': '973318655', 'PhoneNumber': '5417374933', 'StreetAddress': '1500 SW JEFFERSON AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Oregon', 'StateCode': 'OR', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'OR04', 'ORG_UEI_NUM': 'MZ4DYXE1SL98', 'ORG_LGL_BUS_NAME': 'OREGON STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Oregon State University', 'CityName': 'CORVALLIS', 'StateCode': 'OR', 'ZipCode': '973318655', 'StreetAddress': '1500 SW JEFFERSON AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Oregon', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'OR04'}

{'Code': '088Y00', 'Text': 'AM-Advanced Manufacturing'}

2024~100000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435383.xml'}

Conference: Secure and Trustworthy Cyberspace PI Meeting

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Xiaogang (Cliff) Wang', 'PO_EMAI': 'xiawang@nsf.gov', 'PO_PHON': '7032922812'}

The Secure and Trustworthy Cyberspace (SaTC) program, a flagship initiative by the National Science Foundation (NSF), addresses critical cybersecurity challenges from a socio-technical perspective. By delving into deep scientific and engineering issues and considering human behaviors, SaTC aims to advance the field of cybersecurity and privacy. The PI meeting will highlight research accomplishment made by the SaTC funded researchers and create a venue to stimulate coordination and collaboration amongst SaTC PIs working on different topic areas and cross disciplines. Breakout sessions, and networking opportunities will foster creativity and help carve out novel research directions. PIs can explore interdisciplinary research opportunities beyond their own study domains. Two-day intense interactions among researchers from different disciplines will lead to new insights, cultivate new collaborations, and help create new research ideas on improving education, recruitment, and career development in cybersecurity.<br/><br/>The proposal seeks PI support for developing the program for the two-day bi-annual PI meeting to bring together researchers from across the Secure and Trustworthy Cyberspace (SaTC) program in the fall of 2024. The PI will serve on the organizing committee to develop the 2-day PI meeting program who includes tasks such as identifying speakers, defining breakout topics, as well as selecting highlighted NSF projects.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/14/2024

07/14/2024

None

Grant

47.070

1

4900

4900

2435424

{'FirstName': 'Alvaro', 'LastName': 'Cardenas', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alvaro A Cardenas', 'EmailAddress': 'alvaro.cardenas@ucsc.edu', 'NSF_ID': '000641570', 'StartDate': '07/14/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'ZipCode': '950641077', 'PhoneNumber': '8314595278', 'StreetAddress': '1156 HIGH ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'CA19', 'ORG_UEI_NUM': 'VXUFPE4MCZH5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA SANTA CRUZ', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-Santa Cruz', 'CityName': 'SANTA CRUZ', 'StateCode': 'CA', 'ZipCode': '950641077', 'StreetAddress': '1156 HIGH ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'CA19'}

{'Code': '806000', 'Text': 'Secure &Trustworthy Cyberspace'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435424.xml'}

IUCRC Planning Grant University of Arkansas: Center for Infrastructure Security in the Era of AI (ISEAI)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Mohan Kumar', 'PO_EMAI': 'mokumar@nsf.gov', 'PO_PHON': '7032927408'}

This Industry University Cooperative Research Center (IUCRC) award funds the planning phase of the University of Arkansas (UA) in their activities to join the proposed Center for Infrastructure Security in the Era of AI (ISEAI). George Mason University (GMU) is the lead site of the Phase I proposal for creating ISEAI. After successful completion of the planning phase, the (UA) proposers will be eligible to submit a site addition proposal to join an existing IUCRC. The ISEAI seeks to promote widespread adoption of its research outcomes, thereby improving national security and resilience against threats.<br/><br/>When realized, the ISEAI Center will conduct applied research at the forefront of infrastructure security using advanced AI techniques, significantly contributing to the intellectual landscape. It aims to generate cutting-edge insights and solutions that address current challenges and deepen the foundational understanding of evolving threats from traditional and AI-enabled malicious actors. By developing practical solutions, the ISEAI Center effectively bridges theoretical advancements with real-world applications. This planning grant will help the UA site enhance research and education at the intersection of infrastructure security and AI.<br/><br/>When created, the ISEAI Center will have substantial societal impact by enhancing the resilience of critical infrastructure systems. Through innovative solutions and active student involvement at all levels, the Center will contribute to workforce development and foster a skilled talent pool. Furthermore, ISEAI will commit to technology advancement and transfer, integration of research outcomes into practical industry applications, drive innovation and economic growth and address societal needs, thereby bolstering national security, resilience, and well-being. This planning grant will facilitate closer interactions between faculty and students at UA, with industry.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.070

1

4900

4900

2435427

[{'FirstName': 'Christopher', 'LastName': 'Farnell', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Christopher P Farnell', 'EmailAddress': 'cfarnell@uark.edu', 'NSF_ID': '000845873', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Dong', 'LastName': 'Jin', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Dong Jin', 'EmailAddress': 'dongjin@uark.edu', 'NSF_ID': '000654118', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Arkansas', 'CityName': 'FAYETTEVILLE', 'ZipCode': '727013124', 'PhoneNumber': '4795753845', 'StreetAddress': '1125 W MAPLE ST STE 316', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Arkansas', 'StateCode': 'AR', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_ORG': 'AR03', 'ORG_UEI_NUM': 'MECEHTM8DB17', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF ARKANSAS', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Arkansas', 'CityName': 'FAYETTEVILLE', 'StateCode': 'AR', 'ZipCode': '727013124', 'StreetAddress': '1125 W MAPLE ST STE 316', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Arkansas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '03', 'CONGRESS_DISTRICT_PERF': 'AR03'}

[{'Code': '171400', 'Text': 'Special Projects - CNS'}, {'Code': '576100', 'Text': 'IUCRC-Indust-Univ Coop Res Ctr'}]

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435427.xml'}

Conference: NSF:FOCS Conference Student and Postdoc Travel Support

NSF

10/01/2024

09/30/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Peter Brass', 'PO_EMAI': 'pbrass@nsf.gov', 'PO_PHON': '7032922182'}

The Institute of Electrical and Electronics Engineers (IEEE) Symposium on Foundations of Computer Science (FOCS) is one of the premier annual research conferences that cover the breadth of theoretical computer science. It is a conference of very long standing that has continued to play a formative role in the field; it is also at the leading edge of connections made to other areas. This project aims to increase the impact of this conference on students and postdoctoral researchers, particularly those from under-represented groups, by encouraging and enabling their participation, especially in cases where travel expenses would otherwise preclude their attendance.<br/><br/>Concretely, this project assists US-based students and postdoctoral fellows in attending the 2024 Annual FOCS conference, sponsored by the IEEE Computer Society Technical Committee on Mathematical Foundations of Computing (TCMF). The coming FOCS will take place in Chicago, IL, October 27-30, 2024. As computing becomes ubiquitous, it is crucial to expand the participation of young scholars in cutting-edge research. FOCS has served as one of the most important venues for groundbreaking research in theoretical computer science – and, increasingly, as a key ambassador to other areas within and outside computer science. We anticipate the conference presentations and discussions will expose students and postdoctoral researchers to a broad set of fundamental questions and ideas. We expect the community to benefit in turn, as such junior researchers have contributed substantially to the growth of theoretical computer science over the years. With an emphasis on junior scholars in need, supporting the participation of junior researchers from underrepresented populations in the stimulating exchange of ideas benefits all conference attendees. As the tools and techniques from theoretical computer science (such as novel models, algorithms, impossibility results, and unexpected connections in data science and machine learning) are becoming vital to several domains inside and outside computer science, it is anticipated that such broader participation of junior researchers will benefit society at large.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/05/2024

08/05/2024

None

Grant

47.070

1

4900

4900

2435435

{'FirstName': 'Rocco', 'LastName': 'Servedio', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rocco A Servedio', 'EmailAddress': 'rocco@cs.columbia.edu', 'NSF_ID': '000232661', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'ZipCode': '100277922', 'PhoneNumber': '2128546851', 'StreetAddress': '615 W 131ST ST', 'StreetAddress2': 'MC 8741', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'F4N1QNPB95M4', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100277922', 'StreetAddress': '615 W 131ST ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}

{'Code': '779600', 'Text': 'Algorithmic Foundations'}

2024~17000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435435.xml'}

IUCRC Planning Grant George Mason University: Center for Climate Risk Applications (CCRA)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': 'bransom@nsf.gov', 'PO_PHON': '7032927792'}

As human-emitted greenhouse gas pollution warms the planet and changes the dynamics of the climate system, losses due to weather extremes and their impacts on human life and property has become a significant and costly challenge. Reliance on historical records with outdated climate states, coarse model resolution, and incongruency between the spatiotemporal scale of impacts exacerbates the problem and presents serious difficulties for the insurance and finance sectors that rely on accurate assessment of natural perils and the corresponding uncertainties around their frequency, intensity, and duration. This knowledge is required to cover climate disaster related losses that, annually, reach well into tens to hundreds of billions of dollars. To address this challenge, three institutions: George Mason University, the Massachusetts Institute of Technology, and the City University of New York have come together to plan an industry-university cooperative research center that addresses the critical, high priority needs of the insurance and finance sectors, both of which are wrestling with uncertainties in assessing risks and damages due to climate-related disasters. Center research thrusts include: (1) improving climate predictions at spatiotemporal scales needed by the insurance and finance industries; (2) modeling the catastrophic impacts of natural perils to critical infrastructure systems; and (3) quantifying how the local environment modifies the frequency, intensity, and impact of weather-related natural perils on people and property. Broader impacts of the Center would include increased national economic stability by providing better and more reliable tools for assessing climate risk; training the next generation of climate science, engineering, and policy professionals able to tackle the challenges that a changing climate poses to the nation; and broadening the diversity of underrepresented groups in climate disaster modeling field.<br/><br/>Research conducted by the Center for Climate Risk Applications, now in the planning phase, will focus on addressing existing gaps on the impact of climate change on a range of natural perils by analyzing state-of-the-art climate model ensembles, improving existing models, and advancing the science of integration between climate modeling and asset-scale risks. Research will analyze and improve the output of climate models at the actionable spatial and temporal scales required by the insurance and finance sectors of the economy. The Center will also develop new methods for downscaling hazard information to asset-scale granularity, while quantifying uncertainties of year-to-decadal climate predictions. Additional work will address the sensitivity of interconnected infrastructure systems to a changing landscape of natural perils and the potential for disruption of critical services and supply/value chains. Natural disasters impact people, not just infrastructure; thus, the Center, presently in the planning stage will also focus on how public policy and regulation impacts the insurance of properties, as well as how existing frameworks for decision-making around these perils inform resilience efforts in the private and public sectors. The Center's education and outreach activities will help enable and maintain healthy insurance and reinsurance markets to promote economic stability and growth in the face of severe threats from climate change to life and property. It will also develop a diverse, knowledgeable, and capable workforce necessary to quantify risks of climate change for those owning assets that need protection as well as the need to improve their ability to understand and predict risks and create policies, standards, and incentives that reduce the risks of loss due to climate change. The George Mason University contribution to the Center brings its leadership in climate dynamics, infrastructure risk, and resilience that complements the center-wide research agenda that advances the science connecting climate modeling with risk and loss models used in the private and public sectors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/22/2024

08/22/2024

None

Grant

47.050

1

4900

4900

2435436

[{'FirstName': 'James', 'LastName': 'Kinter', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'James Kinter', 'EmailAddress': 'ikinter@gmu.edu', 'NSF_ID': '000567815', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Natalie', 'LastName': 'Burls', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Natalie Burls', 'EmailAddress': 'nburls@gmu.edu', 'NSF_ID': '000666240', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Luis', 'LastName': 'Ortiz', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Luis E Ortiz', 'EmailAddress': 'lortizur@gmu.edu', 'NSF_ID': '000751316', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Fengxiu', 'LastName': 'Zhang', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Fengxiu Zhang', 'EmailAddress': 'fzhang22@gmu.edu', 'NSF_ID': '000857075', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Edward', 'LastName': 'Oughton', 'PI_MID_INIT': 'J', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Edward J Oughton', 'EmailAddress': 'eoughton@gmu.edu', 'NSF_ID': '000853230', 'StartDate': '08/22/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}

{'Code': 'Y17300', 'Text': None}

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435436.xml'}

Conference: The AI and Menopause Workshop: Understanding Needs and Exploring Innovation

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Goli Yamini', 'PO_EMAI': 'gyamini@nsf.gov', 'PO_PHON': '7032925367'}

This award supports a workshop on Artificial Intelligence (AI) to advance knowledge of menopause. Women's health has been historically under-researched, with women excluded from most randomized clinical trials (RCTs) prior to 1993, creating significant gaps in sex-specific clinical data and treatments. This exclusion means women are often treated based on data obtained from men, despite known sex differences in many diseases. As such, critical gaps exist in understanding menstrual health and menopause, with little research on the long-term impact of menopause on the health of women, which treatments are successful for which individuals, and more generally how to support women with their day-to-day management of menopause. Since the timing of menopause is concordant with the timing of the development of many chronic diseases in women, this is critical to understand. AI presents new opportunities to address these gaps by analyzing complex health data like those of electronic health records, wearable devices, and self-tracking apps, and in turn elucidate new knowledge about the health of women that traditional research methods might miss. This could lead to personalized treatments and better management strategies overall. Furthermore, human-centered AI approaches have the potential to help create safe, robust, and equitable solutions to support women and their providers in the management of menopause. <br/><br/>The workshop will bring researchers and domain experts from multiple disciplines centered around women's health together with AI and human-centered AI researchers. The workshop participants will identify research gaps, explore research opportunities, and develop a strategic roadmap for research at the intersection of AI and women's health, specifically menopause. The workshop will facilitate discussions on state-of-the-art computational approaches and intelligent interactive systems, highlighting both opportunities and challenges in applying these technologies to women's health. Key issues such as scientific data sparsity and biased observational datasets will be addressed, as well as benchmarks and evaluation frameworks that align with current menopause research.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/09/2024

07/09/2024

None

Grant

47.070

1

4900

4900

2435444

{'FirstName': 'Noemie', 'LastName': 'Elhadad', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Noemie Elhadad', 'EmailAddress': 'noemie.elhadad@columbia.edu', 'NSF_ID': '000161576', 'StartDate': '07/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'ZipCode': '100277922', 'PhoneNumber': '2128546851', 'StreetAddress': '615 W 131ST ST', 'StreetAddress2': 'MC 8741', 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_ORG': 'NY13', 'ORG_UEI_NUM': 'F4N1QNPB95M4', 'ORG_LGL_BUS_NAME': 'THE TRUSTEES OF COLUMBIA UNIVERSITY IN THE CITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Columbia University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100323720', 'StreetAddress': '622 West 168th Street', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '13', 'CONGRESS_DISTRICT_PERF': 'NY13'}

{'Code': '801800', 'Text': 'Smart and Connected Health'}

2024~75000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435444.xml'}

Conference: AI Aspirations

NSF

09/01/2024

02/28/2025

{'Value': 'Standard Grant'}

{'Code': '15010000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TF', 'LongName': 'Technology Frontiers'}}

{'SignBlockName': 'Kerstin Mukerji', 'PO_EMAI': 'kmukerji@nsf.gov', 'PO_PHON': '7032925390'}

The AI Inspirations conference focuses on emerging research and current developments in artificial intelligence (AI). This conference will identify cross-sector and cross-agency efforts within the domain of AI research and development (R&D) as they relate to both societal and economic impact as well as national security. In addition, this event aims to be responsive to the recent White House Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence (AI EO). <br/><br/>Johns Hopkins University (JHU) will convene 300 science and technology leaders, policymakers, and researchers to share current efforts in AI R&D and identify effective strategies related to AI R&D translation within the U.S. The proposed event will consist of panel discussions on critical topics, technical demonstrations, and plenary sessions designed to showcase and further accelerate the development of responsible and secure AI solutions. Topics to be discussed during this conference will include accurate weather forecasts, resilient power grids, accelerated drug development, personalized didactive learning tools, transformative infrastructure, rapid design of materials for semiconductor manufacturing, and effective/efficient government services.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.084

1

4900

4900

2435452

{'FirstName': 'Alexis', 'LastName': 'Battle', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Alexis Battle', 'EmailAddress': 'ajbattle@jhu.edu', 'NSF_ID': '000963945', 'StartDate': '08/20/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'ZipCode': '212182608', 'PhoneNumber': '4439971898', 'StreetAddress': '3400 N CHARLES ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MD07', 'ORG_UEI_NUM': 'FTMTDMBR29C7', 'ORG_LGL_BUS_NAME': 'THE JOHNS HOPKINS UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Johns Hopkins University', 'CityName': 'BALTIMORE', 'StateCode': 'MD', 'ZipCode': '212182608', 'StreetAddress': '3400 N CHARLES ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MD07'}

{'Code': '306Y00', 'Text': 'TIP-CHIPS KTA-1 AI-ML'}

2024~99776

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435452.xml'}

EAGER: Investigating linkages between increased occurrences of kidney disease and the use of Gulf Coastal plain, lignite-bearing aquifers for domestic water supplies

NSF

07/15/2024

06/30/2026

{'Value': 'Standard Grant'}

{'Code': '06010000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'RISE', 'LongName': 'Div of Res, Innovation, Synergies, & Edu'}}

{'SignBlockName': 'Barbara Ransom', 'PO_EMAI': 'bransom@nsf.gov', 'PO_PHON': '7032927792'}

Lignite is a low rank of coal that is abundant in most Gulf Coastal plain aquifers and has been shown to cause increased occurrences of kidney disease on the Balkan Peninsula of eastern Europe and in Texas, Arkansas, and Louisiana. Mississippi led the nation in kidney disease mortality from 2015-2020 and was second in the nation in 2021. This early concept research project will collect water chemistry data throughout the state of Mississippi and will perform a suite of geospatial statistical analyses on the collected well water data and existing datasets from the US Geological Survey and from the medical sector and other sources to see if ground water from Gulf Coastal Plain aquifers can be linked to kidney disease in Mississippi. Broader impacts of this research is relevant for all residents of Mississippi and potentially residents of all Gulf Coastal Plain states who obtain their water from ground water wells. If a correlation is found, the results of this research can be used to develop mitigation strategies and could identify zones within specific aquifers or specific geographic regions that should be avoided as domestic water supply sources.<br/><br/>Climate-related drought and unpredictable rainfall patterns have led to increasing reliance on groundwater for agricultural irrigation in the Gulf Coastal Plain resulting in significant increases in annual withdrawals from aquifers that are also used for domestic water supplies via municipal and private drinking water wells. Most Gulf Coastal Plain aquifers have naturally occurring lignite, which has been shown to cause increased rates of kidney disease in other parts of the US and world. Mississippi’s mortality rates for kidney disease are among the highest in the nation; but it is unknown if this high rate may be related to the presence of lignite in Gulf Coastal Plain aquifers or due to some other cause. This project applies a variety of machine learning algorithms and techniques on datasets that include water well construction data (location, depth of screened interval, age), health data from the State of Mississippi Medicare database, U.S. Census data, and geochemistry results from a new reconnaissance groundwater survey this project will complete. Goals are to see if there is a statistical correlation between increased rates of kidney disease and the use of lignite-bearing ground water aquifers. Kidney health data will be filtered and classified by a medical doctor specializing in renal functions. Analyses will initially be done for each county in the state. The project funds a Masters-level student in geology at the University of Mississippi which is in an EPSCoR state. The student will learn multidisciplinary skills in geoscience and human health, including: (1) importing and managing data in a geographic information system, (2) performing geospatial analyses techniques; (3) learning how to integrate datasets into machine learning algorithms and how to train AI for neural network analyses on a supercomputer; (4) engaging and interacting with a large cross section of society through seeking permission to sample domestic wells throughout the state; and (5) sampling protocols and techniques for collection of data from water wells, including maintaining chain of custody documentation. Project results may have implications for millions of residents in states across the Mississippi Gulf Coastal Plain states (i.e., Alabama and Georgia) who use groundwater for drinking water. It many also have impact on states such as West Virginia, Kentucky, and Pennsylvania with significant coal-mining industries that have aquifers where there is an intersection of domestic water sources and coal mining activities.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/11/2024

07/11/2024

None

Grant

47.050

1

4900

4900

2435472

{'FirstName': 'Ronald', 'LastName': 'Counts', 'PI_MID_INIT': 'C', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Ronald C Counts', 'EmailAddress': 'rcounts@olemiss.edu', 'NSF_ID': '000835830', 'StartDate': '07/11/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Mississippi', 'CityName': 'UNIVERSITY', 'ZipCode': '386779704', 'PhoneNumber': '6629157482', 'StreetAddress': '113 FALKNER', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Mississippi', 'StateCode': 'MS', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'MS01', 'ORG_UEI_NUM': 'G1THVER8BNL4', 'ORG_LGL_BUS_NAME': 'THE UNIVERSITY OF MISSISSIPPI', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Mississippi', 'CityName': 'UNIVERSITY', 'StateCode': 'MS', 'ZipCode': '386779704', 'StreetAddress': '113 FALKNER', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Mississippi', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'MS01'}

{'Code': '300Y00', 'Text': 'Climate Impact on Human Health'}

2024~300000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435472.xml'}

IUCRC Planning Grant University of Wyoming: Center for AI/ML driven Research in Infrastructure Trust Assurance and Sustainability (AMRITAS)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05050000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CNS', 'LongName': 'Division Of Computer and Network Systems'}}

{'SignBlockName': 'Mohan Kumar', 'PO_EMAI': 'mokumar@nsf.gov', 'PO_PHON': '7032927408'}

This planning phase award to the University of Wyoming (UW) will explore the feasibility of a partner site of the proposed Industry University Cooperative Center (IUCRC) called AI/ML driven Research in Infrastructure Trust Assurance and Sustainability (AMRITAS). The project spans critical sectors such as energy, finance, agriculture, transportation, and defense. The Phase I project proposal for creating the AMRITAS center is led by the Colorado State University (CSU). After successful completion of the planning phase, the (UW) proposers will be eligible to submit a site addition proposal to join an existing IUCRC. This project supports NSF’s mission to promote scientific progress, enhance national health, prosperity, and welfare, and secure national defense.<br/><br/>UW’s research within AMRITAS will focus on developing resilient infrastructure solutions that mitigate risks from random disturbances and intentional adversarial threats. By leveraging cutting-edge artificial intelligence (AI) and machine learning (ML) technologies, UW seeks to promote safe, secure, and reliable infrastructures while advancing ecological sustainability and social equity. Key objectives include ensuring the trustworthiness of AI/ML models by addressing data validity, quality, authenticity, and bias, as well as enhancing the collaboration between AI/ML systems and humans. <br/><br/>When realized, the UW partner site aims to tackle critical challenges in infrastructure development and sustainability across Wyoming and neighboring regions. By integrating research internships and industry collaborations, UW seeks to cultivate a skilled workforce equipped to address emerging infrastructure and cybersecurity challenges. The project will also enhance environmental sustainability, reduce energy risks, and promote social equity in infrastructure development.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/08/2024

08/19/2024

None

Grant

47.070

1

4900

4900

2435474

[{'FirstName': 'Gabrielle', 'LastName': 'Allen', 'PI_MID_INIT': 'D', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Gabrielle D Allen', 'EmailAddress': 'gdallen@uwyo.edu', 'NSF_ID': '000494109', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Milan', 'LastName': 'Zlatkovic', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Milan Zlatkovic', 'EmailAddress': 'mzlatkov@uwyo.edu', 'NSF_ID': '000740463', 'StartDate': '08/08/2024', 'EndDate': '08/19/2024', 'RoleCode': 'Former Co-Principal Investigator'}, {'FirstName': 'Nga', 'LastName': 'Nguyen', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Nga Nguyen', 'EmailAddress': 'nga.nguyen@uwyo.edu', 'NSF_ID': '000799971', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Diksha', 'LastName': 'Shukla', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Diksha Shukla', 'EmailAddress': 'dshukla@uwyo.edu', 'NSF_ID': '000834967', 'StartDate': '08/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}]

{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'ZipCode': '820712000', 'PhoneNumber': '3077665320', 'StreetAddress': '1000 E UNIVERSITY AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Wyoming', 'StateCode': 'WY', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_ORG': 'WY00', 'ORG_UEI_NUM': 'FDR5YF2K32X5', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF WYOMING', 'ORG_PRNT_UEI_NUM': 'FDR5YF2K32X5'}

{'Name': 'University of Wyoming', 'CityName': 'LARAMIE', 'StateCode': 'WY', 'ZipCode': '820712000', 'StreetAddress': '1000 E UNIVERSITY AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Wyoming', 'CountryFlag': '1', 'CONGRESSDISTRICT': '00', 'CONGRESS_DISTRICT_PERF': 'WY00'}

[{'Code': '171400', 'Text': 'Special Projects - CNS'}, {'Code': '576100', 'Text': 'IUCRC-Indust-Univ Coop Res Ctr'}]

2024~20000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435474.xml'}

Mutant evolution in spatially structured, hierarchical populations

NSF

11/01/2023

06/30/2025

{'Value': 'Continuing Grant'}

{'Code': '03040000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'DMS', 'LongName': 'Division Of Mathematical Sciences'}}

{'SignBlockName': 'Zhilan Feng', 'PO_EMAI': 'zfeng@nsf.gov', 'PO_PHON': '7032927523'}

Evolutionary theory for asexual populations seeks to understand how and why genetic change happens in a variety of contexts, from unicellular organisms over generations, to aging and disease of multicellular organisms within the lifespan of a single individual (somatic evolution). While the principles of mutant evolution in homogeneous populations are well-understood and are commonly part of textbooks, they do not directly apply to any realistic population with a spatial, hierarchical structure (such as stem cells that maintain the tissue and more differentiated cells that perform tissue function). These features are, however, a common theme of cell dynamics in tissues of higher organisms, as well as microbial populations such as biofilm forming bacteria, which are also characterized by both spatial and hierarchical structure (cell sub-populations with different specializations). This research project will extend fundamental laws of evolution to be applicable across a much greater variety of biological systems. The mathematical theory will be applied to experimental data that follow the evolution of cells in a mouse model of Rhabdomyosarcoma, which is a pediatric cancer. Finally, the project will develop a new mentoring program that facilitates interactions between students and professors, geared especially towards underrepresented students.<br/><br/>A large mathematical literature exists about mutant spread and invasion, focusing on measures such as the mutant fixation probability or the time to mutant fixation in constant populations, as well as mutant load in growing populations. Scaling laws of evolutionary dynamics have been derived, including the equilibrium population density in spatial models, the rate of stochastic tunneling (double-mutant generation from a minority of single mutants), and the mutant content in expanding colonies. In various biological scenarios, however, cells and organisms evolve in more complex settings than those traditionally considered by evolutionary theory. Of particular importance are spatially structured, hierarchically organized cell populations that are regulated by signaling mechanisms. Examples include tissues consisting of stem and more differentiated cells, solid tumors, and biofilms containing bacterial cells with specialized functions. A comprehensive evolutionary theory for such population structures currently does not exist. This project seeks to mathematically define evolutionary scaling laws for spatially structured populations that are hierarchically organized and contain regulatory feedback loops that control cell fate decisions. This will be done by (a) developing efficient numerical methods that describe spatially expanding, evolving populations, and (b) deriving laws of spatial population dynamics, including rates of fitness valley crossing and scaling laws for the mutant load for different mutant types. The evolutionary theory will be applied to data on cellular evolution in Rhabdomyosarcoma mouse xenografts, which are characterized by both spatial and hierarchical structure.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/02/2024

07/02/2024

None

Grant

47.049

1

4900

4900

2435484

{'FirstName': 'Natalia', 'LastName': 'Komarova', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Natalia Komarova', 'EmailAddress': 'nkomarova@ucsd.edu', 'NSF_ID': '000485742', 'StartDate': '07/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}

{'Code': '733400', 'Text': 'MATHEMATICAL BIOLOGY'}

2022~116812

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435484.xml'}

CAREER: Catalytic Resonance-Enhanced Activation of Hydrocarbon Resources

NSF

01/01/2024

08/31/2026

{'Value': 'Continuing Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Rohit Ramachandran', 'PO_EMAI': 'rramacha@nsf.gov', 'PO_PHON': '7032927258'}

Leveraging the recent abundance of U.S. shale gas resources as a chemical production feedstock requires the use of catalytic upgrading strategies. Constraints related to chemical composition and geographical distribution of both the feedstocks and products require the development of innovative catalytic strategies that can take advantage of these new resources. Motivated by the continuous growth of cost-competitive renewable electric power, the use of electrochemical strategies to enable the activation of hydrocarbon resources provides a unique opportunity to reduce the environmental impact and cost of chemical manufacturing by avoiding the high pressures and temperatures synonymous with thermally driven chemical transformations. Furthermore, the electrochemical approach is more resistant to major disruption events that pose resilience and safety threats in traditional chemical manufacturing supply chains. Therefore, the development of electrically driven chemical reaction strategies in this research program has significant transformative potential. Direct electrochemical catalytic upgrading of hydrocarbon resources, however, currently is limited by both slow reaction rates and poor selectivity to desired products. This study will advance the development of catalytic resonance, whereby the energetics of a catalyst is modulated in time to maximize the reaction rate and selectivity towards the desired product. This study will integrate concepts of sustainable chemical transformation, renewable energy sources, and catalytic kinetics into an educational plan that will engage students both at UMass and the surrounding area. The impact of outreach efforts will be expanded by developing educational online content, using simple and effective teaching techniques to communicate the fundamental science behind energy related applications.<br/><br/>This study will focus on developing a fundamental understanding of catalytic resonance for the electrochemical oxidation of hydrocarbons into value-added oxygenates. While renewable and cost-effective energy to drive the electrochemical reactions is readily available, the rate of catalytic turnover associated with the electrochemical oxidation of hydrocarbons (e.g., alkanes, alkenes) limits the approach. Metal catalysts that do exhibit appreciable electrocatalytic activity are plagued by the lack of selectivity to partial oxidation products due to the over-oxidation of hydrocarbons into carbon dioxide as an undesirable product. Under steady-state conditions, the challenges to catalytic activity and selectivity share a similar origin: balancing the necessary adsorbate coverages, kinetic driving force, and the combination of faradaic and non-faradaic elementary steps involved in the catalytic cycle. Controlled energetic oscillations of the catalytic working electrode decouples the rate-determining factors, allowing for their independent tuning by accessing non-equilibrium states that cannot be sustained under static conditions. While this study will focus on hydrocarbon oxidation, the work will develop the understanding and capabilities needed for extending the concept of catalytic resonance to other important chemical transformations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/21/2024

08/21/2024

None

Grant

47.041

1

4900

4900

2435485

{'FirstName': 'Omar', 'LastName': 'Abdelrahman', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Omar A Abdelrahman', 'EmailAddress': 'abdel@umass.edu', 'NSF_ID': '000790169', 'StartDate': '08/21/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Houston', 'CityName': 'HOUSTON', 'ZipCode': '772043067', 'PhoneNumber': '7137435773', 'StreetAddress': '4300 MARTIN LUTHER KING BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Texas', 'StateCode': 'TX', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_ORG': 'TX18', 'ORG_UEI_NUM': 'QKWEF8XLMTT3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF HOUSTON SYSTEM', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Houston', 'CityName': 'HOUSTON', 'StateCode': 'TX', 'ZipCode': '772043067', 'StreetAddress': 'HOUSTON, TX 772043067', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Texas', 'CountryFlag': '1', 'CONGRESSDISTRICT': '18', 'CONGRESS_DISTRICT_PERF': 'TX18'}

{'Code': '140300', 'Text': 'Proc Sys, Reac Eng & Mol Therm'}

2021~299691

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435485.xml'}

CAREER: CAS: Understanding How Catalyst Modification Impacts Performance Thermodynamic and Kinetic Parameters Pertinent to Catalytic Hydrogenation of Polar Carbonyl Bonds

NSF

08/01/2024

03/31/2025

{'Value': 'Continuing Grant'}

{'Code': '03090000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'CHE', 'LongName': 'Division Of Chemistry'}}

{'SignBlockName': 'Tong Ren', 'PO_EMAI': 'tren@nsf.gov', 'PO_PHON': '7032928840'}

To meet our future energy needs, new chemical reactions that use carbon dioxide (CO2) and other waste products to produce fuels and chemical feedstocks need to be developed. The use of CO2 as a starting material is challenging because it is a gas and not very reactive. Scientists like Dr. Saouma at the University of Utah develop cheap and readily-available catalysts to speed up these reactions. This research project focuses on developing an understanding of how catalyst structure impacts the catalyst performance. This knowledge allows more efficient and effective better catalysts to be prepared. Dr. Saouma is actively engaged in outreach activities that aim to increase female representation in Science, Technology, Engineering, and Math (STEM) fields. She is an instructor and mentor for the College of Science’s ACCESS program, an intensive summer-long program for incoming freshman women that provides them with a comprehensive view of how energy is produced and used in our society. A survey of high school seniors in Utah indicates that prior to college a gender gap exists in students interested in STEM fields. To help offset this, Dr. Saouma is developing an offshoot of ACCESS that is geared towards increasing the number of rising ninth grade women. participating in science.<br/><br/>With funding from the Chemical Structure, Dynamics and Mechanisms-B and the Chemical Catalysis Programs of the Chemistry Division, Dr. Saouma of the University of Utah is developing a fundamental understanding that correlates the thermodynamic properties of a catalyst with catalyst performance for systems that reduce carbonyl bonds. The research measures how ligand and metal identities impact parameters such as hydricity and propensity to add H2 in systems that undergo metal ligand cooperativity and these characteristics are compared through equilibrium measurements. These measurements are also correlated to the catalyst performance in terms of kinetics, mechanism, and scope. Parallel work on developing ligands that are designed to allow separate tuning of the thermodynamic parameters is also under investigation. Dr. Saouma is part of the College of Science’s ACCESS program, whose mission is to increase the representation of women in leadership in the STEM disciplines. In addition to mentoring and instructing the incoming freshman women of ACCESS, Dr. Saouma is developing a sister program that will encompass a summer camp for rising 9th graders, to help address the gender discrepancy in STEM interest that exists amongst high school students in Utah.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.049

1

4900

4900

2435518

{'FirstName': 'Caroline', 'LastName': 'Saouma', 'PI_MID_INIT': 'T', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Caroline T Saouma', 'EmailAddress': 'csaouma@vt.edu', 'NSF_ID': '000728209', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'ZipCode': '240603359', 'PhoneNumber': '5402315281', 'StreetAddress': '300 TURNER ST NW', 'StreetAddress2': 'STE 4200', 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_ORG': 'VA09', 'ORG_UEI_NUM': 'QDE5UHE5XD16', 'ORG_LGL_BUS_NAME': 'VIRGINIA POLYTECHNIC INSTITUTE & STATE UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'M515A1DKXAN8'}

{'Name': 'Virginia Polytechnic Institute and State University', 'CityName': 'BLACKSBURG', 'StateCode': 'VA', 'ZipCode': '240603359', 'StreetAddress': '300 TURNER ST NW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '09', 'CONGRESS_DISTRICT_PERF': 'VA09'}

{'Code': '910200', 'Text': 'CMFP-Chem Mech Funct, and Prop'}

2021~262012

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435518.xml'}

I-Corps: Translation Potential of an End-to-End Solution for Automating 3D Metal Hybrid Printing Processes

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Jaime A. Camelio', 'PO_EMAI': 'jcamelio@nsf.gov', 'PO_PHON': '7032922061'}

The broader impact of this I-Corps project is the development of automated, 3D, hybrid, metal printing software and its associated instrumentation. This technology promises to increase production speeds and reduce costs, making 3D metal printing more accessible and efficient. The technology ensures high-quality printed parts with a reproducible process, targeting demanding applications in the automotive and aerospace industries. Moreover, the process versatility extends to plastic printing and other domains, facilitating rapid prototyping and product development cycles. The innovation promises substantial economic benefits by lowering the cost per part for low-volume production and minimizing slow-moving inventory. The technology aims to optimize material usage and energy consumption, contributing to environmental sustainability, and reducing overall carbon dioxide (CO2) emissions. Ultimately, this project serves as a critical step for transitioning additive manufacturing from prototyping to high-volume production, offering transformative opportunities across various industrial sectors.<br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a smart, automated, 3D printing technology to address challenges inherent in 3D metal additive and hybrid processes, which while flexible, often suffer from high costs and extended production times due to material inconsistencies and variable print quality. This intelligent solution harnesses the full potential of hybrid printing and expands the capabilities for printing 3D components using diverse metal and metal alloy materials. Unlike previous work, this technology automates the 3D printing process using artificial intelligence and machine learning algorithms, eliminating human interaction. It addresses the challenges by providing 3D metal printing resulting in: (1) an efficient printing process that blends machine learning and artificial intelligence to streamline printing, reducing production times and enhancing competitiveness; (2) a cost-effective process that minimizes preprocessing, machine parameter setup, and printing time, improving economic viability; and (3) reproducibility and quality assurance that ensures consistent material properties and reproducible processes through an innovative in situ, quality-controlled, process-enhancing component reliability and quality.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/29/2024

07/29/2024

None

Grant

47.084

1

4900

4900

2435524

{'FirstName': 'Lina', 'LastName': 'Sawalha', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Lina Sawalha', 'EmailAddress': 'lina.sawalha@wmich.edu', 'NSF_ID': '000673016', 'StartDate': '07/29/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Western Michigan University', 'CityName': 'KALAMAZOO', 'ZipCode': '490085200', 'PhoneNumber': '2693878298', 'StreetAddress': '1903 W MICHIGAN AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Michigan', 'StateCode': 'MI', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MI04', 'ORG_UEI_NUM': 'J7WULLYGFRH1', 'ORG_LGL_BUS_NAME': 'WESTERN MICHIGAN UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Western Michigan University', 'CityName': 'KALAMAZOO', 'StateCode': 'MI', 'ZipCode': '490085200', 'StreetAddress': '1903 W MICHIGAN AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Michigan', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MI04'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435524.xml'}

Travel: DELTA H 2024, building international bridges to advance research and EDI in Geomorphology through an immersive meeting in Brazil: Supporting U.S.-based attendees

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '06030000', 'Directorate': {'Abbreviation': 'GEO', 'LongName': 'Directorate For Geosciences'}, 'Division': {'Abbreviation': 'EAR', 'LongName': 'Division Of Earth Sciences'}}

{'SignBlockName': 'Justin Lawrence', 'PO_EMAI': 'jlawrenc@nsf.gov', 'PO_PHON': '7032922425'}

In the study of the Earth’s surface, being able to visit landscapes in different climatic and tectonic settings helps build geoscientists’ scientific intuition about its evolution. Landscapes far from active geologic faults and in tropical regions such as those in Brazil are natural laboratories to study landscape evolution principally associated with the chemical alteration of rocks and soils and climatic fluctuation. These landscapes are also impacted by anthropogenic forcings such as hydroelectric dams, mining dam failures, land use, and forest fires. Consequently, the continent interiors of South America are also fantastic natural settings to study geohazards such as landslides, seasonal and flash floods, debris flows, etc. Despite these characteristics, South Americans are underrepresented in the international cutting-edge Geomorphology community as represented through scientific publications and international collaborations. However, the Geoscience community would clearly benefit from a more connections between international scientific communities. Moreover, as climate changes progress, the greater the portfolio of landscape styles Earth Scientists have visited, the better prepared they can be to develop solutions. This project seeks to contribute to bettering the international exchange of scientific wisdom and help build new collaborative bridges in Geomorphology by funding US based scholars to attend the 2024 DELTA H meeting on Landscape Evolution in the Brazilian highlands of Belo Horizonte, Minas Gerais. <br/><br/>In Brazil and potentially in other South American countries as well, the underrepresentation of geomorphologists in the international cutting-edge geomorphology community is arguably a symptom of several underlying gaps such as 1) the low exposure to Quantitative Geomorphology during undergraduate studies in Geology and Geography majors; 2) a historic disconnect between Geomorphology as a key discipline in Geological sciences; 3) a biased perception that Geomorphology pertains to Quaternary processes only; 4) a biased perception that Geomorphology deals primarily with soils. Student and researcher participants of past DELTA H report the meeting as highly inspiring, transformative, and sparking interest in pursuing academic careers in Geomorphology. Past invited speakers have also highlighted DELTA H’s potential as a hub to recruit highly motivated students. By funding the attendance of U.S.-based students and early-career geomorphologists, this project will foster the feeling of purpose amongst students and professionals while creating international bridges to advance research in Geomorphology through international collaborations.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/08/2024

07/08/2024

None

Grant

47.050

1

4900

4900

2435528

{'FirstName': 'Pedro', 'LastName': 'Val', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Pedro Val', 'EmailAddress': 'pval@qc.cuny.edu', 'NSF_ID': '000939800', 'StartDate': '07/08/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'CUNY Queens College', 'CityName': 'FLUSHING', 'ZipCode': '113671575', 'PhoneNumber': '7189975400', 'StreetAddress': '6530 KISSENA BLVD', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_ORG': 'NY06', 'ORG_UEI_NUM': 'EJABWGUJM228', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'CUNY Queens College', 'CityName': 'FLUSHING', 'StateCode': 'NY', 'ZipCode': '113671575', 'StreetAddress': '6530 KISSENA BLVD', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '06', 'CONGRESS_DISTRICT_PERF': 'NY06'}

{'Code': '745800', 'Text': 'Geomorphology & Land-use Dynam'}

2024~15000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435528.xml'}

Conference: Imagenets4EDA: Towards Open-Source Datasets for AI in Chip Design

NSF

08/01/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Sankar Basu', 'PO_EMAI': 'sabasu@nsf.gov', 'PO_PHON': '7032927843'}

Machine learning (ML) tools and Large Language Models (LLMs) have shown great promise in making the complex task of designing a computer chip design easier, faster and better. However, modern ML tools and LLMs rely on vast quantities of high-quality training data. Unfortunately, much of the data that can be used to train ML models for chip design are held by semiconductor companies who cannot release this data publicly. The paucity of large and good datasets poses a fundamental challenge to progress in this area. Such a challenge was encountered during the early years of the ML boom. At the time, a public dataset of images, ImageNet, played the role of catalyzing progress in the area of ML for image recognition. To mirror this effort for chip design, this project will convene leading experts from academia, industry and government at an “Imagenets4EDA” workshop. Via a sequence of panels, talks, and brainstorming sessions, the goal is to put forth a concrete agenda on how industry, academia and government can work together to achieve the common goal of building the equivalent of the ImageNet dataset for chip design. The outcome will be a concrete action plan that participants will commit to pursue. The organizers will make every effort to ensure that a broad range of voices, including participants from under-represented groups, are invited and heard at the workshop. <br/>Participants will also be encouraged to think about ways to achieve geographic, institutional, and demographic diversity in the group of students and researchers involved in data collection efforts and benchmarking competitions. The project will fund the participation of US-based researchers and students in the workshop.<br/><br/>Recently, ML methods, like generative AI, LLMs and reinforcement learning (RL), have shown remarkable ability in performing a wide range of tasks in hardware design. Their applications in the design of computing stacks promise to revolutionize hardware code generation, system-level, and the electronic design automation (EDA) flow. Yet there is a critical need for datasets and benchmarks to realize this promise. By bringing together a community of experts in this area representing all key stakeholders, the ImageNets4EDA workshop agenda will pursue three synergistic goals. First, gaps in existing datasets will be identified via discussions and analyses of existing datasets, and pinpointing areas where current datasets are lacking. The second goal is an open call to the community---academia, industry and government---to contribute datasets in ways that protect the intellectual property rights of companies, while still providing sufficient quality of data that would enable training of foundation models for EDA. The third direction is a plan to organize benchmarking competitions by deciding one step in the EDA flow, for instance, physical design. ML tools will cut chip design lifecycles, improve productivity of semiconductor designers, and result in faster and lower chips, providing large benefits to US economy and society.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/24/2024

07/24/2024

None

Grant

47.070

1

4900

4900

2435536

{'FirstName': 'Siddharth', 'LastName': 'Garg', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Siddharth Garg', 'EmailAddress': 'sg175@nyu.edu', 'NSF_ID': '000680915', 'StartDate': '07/24/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'ZipCode': '100121019', 'PhoneNumber': '2129982121', 'StreetAddress': '70 WASHINGTON SQ S', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_ORG': 'NY10', 'ORG_UEI_NUM': 'NX9PXMKW5KW8', 'ORG_LGL_BUS_NAME': 'NEW YORK UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'New York University', 'CityName': 'NEW YORK', 'StateCode': 'NY', 'ZipCode': '100121019', 'StreetAddress': '70 WASHINGTON SQ S', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '10', 'CONGRESS_DISTRICT_PERF': 'NY10'}

{'Code': '779800', 'Text': 'Software & Hardware Foundation'}

2024~45693

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435536.xml'}

Conference: Workshop on Designing Accountable Software Systems

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Sol Greenspan', 'PO_EMAI': 'sgreensp@nsf.gov', 'PO_PHON': '7032927841'}

Society is increasingly dependent on software applications, systems, and platforms, as functionality in all aspects of business, government, and everyday life is becoming implemented in software-intensive systems. Whereas people and enterprises have been held accountable to laws, regulations, and societal goals and norms, when implemented through software, now software systems must also work in a way consistent with accountability goals. Software systems need to be designed with legal and regulatory compliance and social norms in mind. The U.S. National Science Foundation (NSF) Designing Accountable Software Systems (DASS) program is supporting research investigating the issues in achieving accountable software systems. Researchers on DASS proposals are a mix of Software Engineering researchers paired with PIs from the social and legal science. The purpose of the DASS workshop is to assess the state of the DASS program and the state of related research at large. In addition to reflecting on the successes and challenges of DASS-related research from the past, the workshop will focus on the emergence and expansion of DASS-like issues in the context of established research fields, such as safety in cyber-physical systems, fairness in artificial intelligence (AI) systems, and privacy and security in cyberspace. The workshop will help grow the DASS community of researchers and provide valuable insights into existing research challenges and future research directions in the field. By improving accountability in software design, the success of building this community can improve how members of society from across socio-cultural and economic backgrounds engage with services across banking, education, healthcare, and transportation, among others.<br/><br/>Designing accountable software systems relies on theory and scientific principles from across the social and behavioral sciences, law, and computer science, including how individuals and groups make decisions, how bias affects decision-making, and how incentives motivate individuals. Legal theory that differentiates compliance from liability and legal processes that produce laws and adjudicate whether individuals and groups are compliant with law all affect how we define accountability. Finally, the technical means to support decision-makers and implement processes must be demonstrably correct and reliable. The software development processes used in practice must take these advances into account. A key challenge is how to nurture collaboration across these varied disciplines. The workshop will create an environment where ideas are presented, developed, discussed and synthesized to orient this cross-disciplinary community around a shared set of scientific objectives, each of which is originated and developed by one or more disciplines and supported by others.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/13/2024

08/13/2024

None

Grant

47.070

1

4900

4900

2435539

{'FirstName': 'Travis', 'LastName': 'Breaux', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Travis Breaux', 'EmailAddress': 'breaux@cs.cmu.edu', 'NSF_ID': '000572505', 'StartDate': '08/13/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}

{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152133815', 'StreetAddress': '5000 FORBES AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}

{'Code': '287800', 'Text': 'Special Projects - CCF'}

2024~258469

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435539.xml'}

Conference: Fall Workshop on Computational Geometry 2024

NSF

10/01/2024

03/31/2025

{'Value': 'Standard Grant'}

{'Code': '05010000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'CCF', 'LongName': 'Division of Computing and Communication Foundations'}}

{'SignBlockName': 'Peter Brass', 'PO_EMAI': 'pbrass@nsf.gov', 'PO_PHON': '7032922182'}

Computational Geometry is the theory of algorithms for geometric problems. Since many of the computations associated with both real and simulated physical systems are geometric in nature, research in computational geometry has been fueled by applications in numerous fields, such as computer graphics, geometric modeling, molecular biology, sensor networks, engineering design, robotics, machine learning, machine vision, data mining, and statistics, to mention just a few. All of these areas are at the forefront of current research activity in computational geometry. The Fall Workshop on Computational Geometry is a two-day meeting of researchers, mostly junior. It is a no-fee meeting whose reach can be thus larger than the major conferences. The Fall Workshop in Computational Geometry series was originally established in 1991 and has since then been held almost every fall. <br/><br/>This award will support around 30 US-based students attending the 31st Annual Fall Workshop on Computational Geometry, November 15-16, 2024, at Tufts University, Medford, Massachusetts.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/05/2024

08/05/2024

None

Grant

47.070

1

4900

4900

2435540

[{'FirstName': 'Joseph S.', 'LastName': 'Mitchell', 'PI_MID_INIT': 'B', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Joseph S. B Mitchell', 'EmailAddress': 'joseph.mitchell@stonybrook.edu', 'NSF_ID': '000364690', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Diane', 'LastName': 'Souvaine', 'PI_MID_INIT': 'L', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Diane L Souvaine', 'EmailAddress': 'diane.souvaine@tufts.edu', 'NSF_ID': '000106963', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Hugo', 'LastName': 'Akitaya', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Hugo A Akitaya', 'EmailAddress': 'hugo_akitaya@uml.edu', 'NSF_ID': '000883858', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Tufts University', 'CityName': 'SOMERVILLE', 'ZipCode': '021442401', 'PhoneNumber': '6176273696', 'StreetAddress': '169 HOLLAND ST', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Massachusetts', 'StateCode': 'MA', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_ORG': 'MA07', 'ORG_UEI_NUM': 'WL9FLBRVPJJ7', 'ORG_LGL_BUS_NAME': 'TRUSTEES OF TUFTS COLLEGE', 'ORG_PRNT_UEI_NUM': 'WL9FLBRVPJJ7'}

{'Name': 'Tufts University', 'CityName': 'SOMERVILLE', 'StateCode': 'MA', 'ZipCode': '021442401', 'StreetAddress': '169 HOLLAND ST', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Massachusetts', 'CountryFlag': '1', 'CONGRESSDISTRICT': '07', 'CONGRESS_DISTRICT_PERF': 'MA07'}

{'Code': '779600', 'Text': 'Algorithmic Foundations'}

2024~15000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435540.xml'}

WORKSHOP: Doctoral Consortium at the 2024 Conference on Accessibility and Computing (ASSETS)

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Ephraim Glinert', 'PO_EMAI': 'eglinert@nsf.gov', 'PO_PHON': '7032924341'}

This is funding to support a Doctoral Consortium (workshop) of approximately nine (9) promising graduate students from U.S. educational institutions to take part in an event that will take place on October 27, 2024, in conjunction with the ACM ASSETS 2024 Conference sponsored by the ACM Special Interest Group on Computers and Accessibility, which is the premier forum for presenting innovative research on the design and use of both mainstream and specialized assistive technologies in support of the needs associated with speech, motor, hearing, and vision impairments, cognitive limitations, emotional and learning disabilities, aging and education in computing accessibility, as well as the professionals who work with these populations, and which will be held in St. John’s, Newfoundland and Labrador on October 27–30. The Doctoral Consortium will provide doctoral students working in the field of assistive technologies and accessibility with a friendly and open forum: to present their research ideas, listen to ongoing work from peer students, and receive constructive feedback; will enable participants to develop a supportive community of scholars and a spirit of collaborative research; will provide students with relevant information about important issues for doctoral candidates and future academics; and will provide a new generation of researchers with information and advice on academic, research,<br/><br/>The ASSETS 2024 Doctoral Consortium provides an opportunity for doctoral students to explore their research interests in an interdisciplinary and international workshop, under the guidance of a panel of distinguished experts in the field. The Doctoral Consortium will also offer discussion groups and the opportunity to learn from individuals who recently completed their PhD. Student participants will make both formal and informal presentations of their work during the Consortium and will receive feedback from the faculty panel. This feedback is designed to help students understand and articulate how their work is positioned relative to related research, whether their topics are adequately focused for thesis research projects, whether their methods are appropriately chosen and adequately applied, and whether their results are appropriately analyzed and presented. This Doctoral Consortium will also help shape ongoing and future research projects aimed at assistive technologies and universal access. A key component of building this community is engaging the next generation of researchers. The Consortium brings PhD students together from diverse backgrounds (e.g., engineering, computing, architecture, and psychology) so that they can see the broader spectrum of research and development approaches to assistive technologies and universal usability. The Consortium also provides exposure to the community in which they can pursue their endeavors.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/03/2024

07/03/2024

None

Grant

47.070

1

4900

4900

2435542

{'FirstName': 'Kristen', 'LastName': 'Shinohara', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Kristen Shinohara', 'EmailAddress': 'kristen.shinohara@rit.edu', 'NSF_ID': '000615487', 'StartDate': '07/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'ZipCode': '146235603', 'PhoneNumber': '5854757987', 'StreetAddress': '1 LOMB MEMORIAL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'J6TWTRKC1X14', 'ORG_LGL_BUS_NAME': 'ROCHESTER INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146235603', 'StreetAddress': '1 LOMB MEMORIAL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}

{'Code': '736700', 'Text': 'HCC-Human-Centered Computing'}

2024~26665

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435542.xml'}

Conference: Quantum Leap Career Nexus Workshop

NSF

08/15/2024

07/31/2025

{'Value': 'Standard Grant'}

{'Code': '03060000', 'Directorate': {'Abbreviation': 'MPS', 'LongName': 'Direct For Mathematical & Physical Scien'}, 'Division': {'Abbreviation': 'OSI', 'LongName': 'Office of Strategic Initiatives (OSI)'}}

{'SignBlockName': 'Tomasz Durakiewicz', 'PO_EMAI': 'tdurakie@nsf.gov', 'PO_PHON': '7032924892'}

Technical Abstract: The quantum science and engineering community is focused on developing protocols and devices that leverage the unique features of quantum mechanics to achieve classically infeasible tasks. Realizing this potential requires highly trained scientists and engineers who are fluent in quantum concepts. More must be done to attract, train, and place emerging talent to meet the needs of a growing market in industry, government, and academia. Populating the growing quantum workforce requires training in science communication, exposure to career pathways, and access to internship and job opportunities. The Institute for Robust Quantum Simulation has developed the Quantum Leap Career Nexus workshop to advance workforce development through internship and job placement. The goal is to facilitate more such placements in the local and regional area, where a multi-university quantum-focused career workshop does not yet exist.<br/><br/>Non-Technical Abstract: This workshop is a direct result of feedback from and was designed by young researchers, who are interested in learning more about career pathways and are eager for opportunities to expand their professional networks, engaging more fully in the quantum industry. The program brings together undergraduates, graduate students, postdoctoral scholars, and early-career professionals to build career skills, establish mentorships, widen networks, learn about emerging career pathways, create new connections between talent and employers in quantum science and engineering, and showcase research and work experience to secure promising placements. It provides career-development training to enhance job-seekers’ marketability through stronger resumes, expanded digital footprints, and improved communication to a non-technical audience. A significant portion of the workshop is dedicated to networking and recruitment activities with potential employers, to help with internship and career placements in quantum science and technology. The location in Prince George’s County, Maryland provides a unique opportunity to leverage the mid-Atlantic region’s diverse population of students and professionals and its abundance of employers across the quantum industry, academia, and<br/>government. In addition to inviting attendees from local, regional, and national partners such as the Institute’s partner universities, other Quantum Leap Challenge Institutes, and other quantum centers, this workshop invites attendees from historically Black colleges and universities and minority-serving institutions. To broaden access to career opportunities in quantum science and technology for students of all backgrounds, the workshop covers travel expenses for at least fifty attendees.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/09/2024

08/09/2024

None

Grant

47.049

1

4900

4900

2435548

[{'FirstName': 'Andrew', 'LastName': 'Childs', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Andrew M Childs', 'EmailAddress': 'amchilds@umd.edu', 'NSF_ID': '000688465', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Zohreh', 'LastName': 'Davoudi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Zohreh Davoudi', 'EmailAddress': 'davoudi@umd.edu', 'NSF_ID': '000846452', 'StartDate': '08/09/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'ZipCode': '207425100', 'PhoneNumber': '3014056269', 'StreetAddress': '3112 LEE BUILDING', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Maryland', 'StateCode': 'MD', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_ORG': 'MD04', 'ORG_UEI_NUM': 'NPU8ULVAAS23', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF MARYLAND, COLLEGE PARK', 'ORG_PRNT_UEI_NUM': 'NPU8ULVAAS23'}

{'Name': 'University of Maryland, College Park', 'CityName': 'COLLEGE PARK', 'StateCode': 'MD', 'ZipCode': '207425100', 'StreetAddress': '3112 LEE BUILDING', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Maryland', 'CountryFlag': '1', 'CONGRESSDISTRICT': '04', 'CONGRESS_DISTRICT_PERF': 'MD04'}

{'Code': '125300', 'Text': 'OFFICE OF MULTIDISCIPLINARY AC'}

2024~41115

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435548.xml'}

Collaborative Research: Do defenses against herbivores and pathogens drive the commonness and rarity of tropical trees at local and regional scales?

NSF

03/15/2024

01/31/2025

{'Value': 'Standard Grant'}

{'Code': '08010000', 'Directorate': {'Abbreviation': 'BIO', 'LongName': 'Direct For Biological Sciences'}, 'Division': {'Abbreviation': 'DEB', 'LongName': 'Division Of Environmental Biology'}}

{'SignBlockName': 'Steven Dudgeon', 'PO_EMAI': 'sdudgeon@nsf.gov', 'PO_PHON': '7032922279'}

The Amazon rainforest is home to a huge number of plant species. Scientists have wondered for a long time why some are so rare and others so common. Perhaps some are better at protecting themselves from insects and diseases. These species could then become unusually common. How do plants protect themselves? Most make special chemicals that can be a potent defense against natural enemies (mostly fungus and insects). Scientists think such chemicals may be especially important in very common species because without extra protection, insects and fungal diseases would spread rapidly in dense populations. This project will test whether plant chemicals can explain how the most common rainforest trees keep from being overwhelmed by their enemies. More generally, it may explain the abundance of different species in different places. This study will also test the role of plant chemicals as defenses against soil pathogens, which are important but poorly known. Data from this project has the potential to generate new medical and agricultural applications. The project will engage and involve low income, first-generation high school students and undergraduates at three universities. Finally, students at those universities will gain essential skills by attending a tropical field biology course with students from Peru and Brazil, and will learn how to do rainforest research. <br/><br/>This project will focus on Protium (Burseraceae), a common and diverse genus of Neotropical trees. Protium species with more diverse and effective anti-enemy defenses are hypothesized to suffer less density-dependent mortality, gaining a strong competitive advantage that should translate into larger populations at the local and regional scale. In the laboratory, metabolomic approaches will assess the diversity of plant secondary metabolites in leaves and roots of Protium in tandem with DNA sequencing to identify how those metabolites influence the presence of fungal pathogens, thus elucidating their role in mediating plant-natural enemy interactions. In the field, a combination of observational and experimental approaches will identify these plant-defense-enemy interactions and quantify their effect on host plant species abundances and the ability of locally and regionally abundant taxa to escape negative density-dependent interactions. This experimental component will be conducted in forest reserves in Iquitos, Peru where permanent plots by long-term collaborators and international institutional partners have been established through previous NSF projects. To investigate how chemical diversity might affect large scale patterns of species abundances in the Amazon basin, this project will also perform systematic surveys across large areas in Peru, Colombia and Brazil to determine how chemistry and plant natural enemy communities change across species’ ranges. Results will provide a critical test of specific chemically-mediated mechanisms thought to control plant-natural enemy interactions, and thus a newly emerging hypothesis about the ecological processes that determine rarity and commonness in high diversity tropical rainforests. Ultimately, this research will yield a deeper understanding of the processes underlying the origin and maintenance of the vast biodiversity of tropical forests.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.074

1

4900

4900

2435550

{'FirstName': 'Diego', 'LastName': 'Salazar', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Diego Salazar', 'EmailAddress': 'dsalazaramor@binghamton.edu', 'NSF_ID': '000590525', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'SUNY at Binghamton', 'CityName': 'BINGHAMTON', 'ZipCode': '139024400', 'PhoneNumber': '6077776136', 'StreetAddress': '4400 VESTAL PKWY E', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_ORG': 'NY19', 'ORG_UEI_NUM': 'NQMVAAQUFU53', 'ORG_LGL_BUS_NAME': 'RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK, THE', 'ORG_PRNT_UEI_NUM': 'GMZUKXFDJMA9'}

{'Name': 'SUNY at Binghamton', 'CityName': 'BINGHAMTON', 'StateCode': 'NY', 'ZipCode': '139024400', 'StreetAddress': '4400 VESTAL PKWY E', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '19', 'CONGRESS_DISTRICT_PERF': 'NY19'}

[{'Code': '112800', 'Text': 'Population & Community Ecology'}, {'Code': '765700', 'Text': 'Integrtv Ecological Physiology'}]

2020~88960

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435550.xml'}

EAGER: Netzero: Exploring the feasibility of generative AI language models to create scalable and equitable building energy models

NSF

10/01/2024

09/30/2026

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Bruce Hamilton', 'PO_EMAI': 'bhamilto@nsf.gov', 'PO_PHON': '7032920000'}

Existing buildings represent a substantial opportunity to reduce energy costs and decarbonize our society. Realizing this goal often requires creating a bottom-up physics-based building energy model (e.g. EnergyPlus) of a particular building to identify and analyze potential energy-efficient retrofit opportunities. Creating a detailed building energy model is a manual, labor-intensive, and expensive process, limiting access to such models for most buildings. The emerging technology of generative artificial intelligence (AI) large language models (LLMs) represents a potentially transformative mechanism to reduce the required labor and costs for creating building energy models, thereby making building energy modeling more accessible to a broad spectrum of the building stock. The overall research objective of this project is to explore the feasibility of generative AI LLMs to create building energy models and understand how this emerging technology can be applied to building decarbonization and energy equity challenges. The two project specific objectives are: 1) Test the feasibility of generative AI LLMs to automate various steps of building energy model creation; 2) Quantify the performance and time tradeoffs between traditional and generative AI-driven building energy models and apply these insights to decarbonization and energy equity challenges.<br/><br/>This project is one of the first to apply the emerging technology of generative AI to the grand challenge of building decarbonization. The project has high-risk elements given the unproven nature of this new technology (large language models) and its application to the domain of building energy modeling. The research also has a “high reward” potential to fundamentally transform current practices in building energy modeling by automating the process of modeling building stock and identifying building energy efficiency and decarbonization solutions. The expected research results are potentially transformative as they would yield fundamental knowledge and quantitative analysis on the dynamics between building energy models and generative AI models. The knowledge created and the associated quantitative analysis will inform methods in both the fields of building science and artificial intelligence. Specifically, this project will yield the following: 1) A feasibility assessment and knowledge of how AI LLMs can automate each step of the building energy modeling process; 2) A quantitative understanding of the performance and time tradeoffs between traditional and generative AI-driven building energy models. This project aims to have a broad impact on the academic and burgeoning industrial communities related to generative AI and building decarbonization. For the academic community, this project will help catalyze a new generation of research spanning building science and artificial intelligence. The project’s impact on the academic community will be further enhanced by publishing data, code, and models to a GitHub repository. For the industrial community, this project aims to catalyze net-zero building heating and cooling by laying the foundation for highly scalable building energy models. The project plans to reach the industrial community by leveraging existing outreach programs by the Stanford Center for Integrated Facility Engineering. Additionally, the project plans to partner with the Stanford Building Decarbonization Learning Accelerator to disseminate research and provide training to small firms that are leading decarbonization efforts in disadvantaged communities. The project will also have strong pedagogical broader impacts as the experiments will be conducted in PI Jain’s course on building energy modeling. Students in his course will gain exposure and hands-on experience with generative AI and its applications to building science.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/10/2024

07/10/2024

None

Grant

47.041

1

4900

4900

2435567

{'FirstName': 'Rishee', 'LastName': 'Jain', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Rishee Jain', 'EmailAddress': 'risheej@stanford.edu', 'NSF_ID': '000655241', 'StartDate': '07/10/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Stanford University', 'CityName': 'STANFORD', 'ZipCode': '943052004', 'PhoneNumber': '6507232300', 'StreetAddress': '450 JANE STANFORD WAY', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_ORG': 'CA16', 'ORG_UEI_NUM': 'HJD6G4D6TJY5', 'ORG_LGL_BUS_NAME': 'THE LELAND STANFORD JUNIOR UNIVERSITY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Stanford University', 'CityName': 'STANFORD', 'StateCode': 'CA', 'ZipCode': '943052004', 'StreetAddress': '450 JANE STANFORD WAY', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '16', 'CONGRESS_DISTRICT_PERF': 'CA16'}

{'Code': '764300', 'Text': 'EnvS-Environmtl Sustainability'}

2024~294457

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435567.xml'}

The HBCU CHIPS Network: A Path for Creating, Preparing, and Increasing Research, Innovation Capacity and an Inclusive Microelectronics Workforce

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '11060000', 'Directorate': {'Abbreviation': 'EDU', 'LongName': 'Directorate for STEM Education'}, 'Division': {'Abbreviation': 'EES', 'LongName': 'Div. of Equity for Excellence in STEM'}}

{'SignBlockName': 'Tori Rhoulac Smith', 'PO_EMAI': 'tosmith@nsf.gov', 'PO_PHON': '7032922315'}

The HBCU Chips Network is a collaborative effort, involving Historically Black Colleges and Universities (HBCUs), government agencies, academia, and industry, that will serve as a national resource for semiconductor research and education. Through a multidisciplinary approach, the Network will facilitate research innovations, resolve long-standing disparities in facilities, build domestic capacity, provide shared accessibility across Network stakeholders, and broaden participation in the microelectronics workforce. This project allows for establishment of a sustainable, administrative infrastructure and protocols to 1) support the multi-institutional research effort and 2) address national microelectronics-related research and development and workforce development needs. This project is funded by the NSF Eddie Bernice Johnson INCLUDES Initiative to advance the goals of the CHIPS and Science Act of 2022. This project is also funded by the Historically Black Colleges and Universities Undergraduate Program (HBCU-UP), which provides awards to strengthen STEM undergraduate education and research at HBCUs.<br/><br/>The Network objective is to advance leadership in microelectronics technology by leveraging the collective research expertise, capabilities, infrastructure, and core competencies of HBCUs. Activities address the design and fabrication of chips at various HBCU institutions, including: (1) two-dimensional (2D) semiconductor field-effect transistors and optoelectronic devices (Jackson State University and North Carolina A&T State University); (2) high-efficiency thermoelectric materials and integrated devices for the application of power generation and solid-state cooling (Alabama A&M State University); (3) 2D-3D material development and their integration (Delaware State University); (4) semiconductor packaging using composite materials of polymer and boron nitride nanotube composites (Norfolk State University); (5) the integration of underfill and heat spreader materials for heterogeneous packaging applications (North Carolina A&T State University); and (6) the packaging of HBCU chips into systems (Georgia Institute of Technology). To cultivate a diverse and skilled workforce for the national semiconductor industry, the Network supports student research and the development of specialized curricula in semiconductor design, fabrication, and related fields, along with internship and research opportunities in collaboration with industry partners.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/05/2024

08/05/2024

None

Grant

47.076

1

4900

4900

2435570

[{'FirstName': 'George', 'LastName': 'White', 'PI_MID_INIT': 'E', 'PI_SUFX_NAME': 'Jr', 'PI_FULL_NAME': 'George E White', 'EmailAddress': 'george.white@gatech.edu', 'NSF_ID': '000847253', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Talitha', 'LastName': 'Washington', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Talitha Washington', 'EmailAddress': 'twashington@cau.edu', 'NSF_ID': '000621452', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Frances', 'LastName': 'Williams', 'PI_MID_INIT': 'R', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Frances R Williams', 'EmailAddress': 'fwilliams@cau.edu', 'NSF_ID': '000239649', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}, {'FirstName': 'Shyam', 'LastName': 'Aravamudhan', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Shyam Aravamudhan', 'EmailAddress': 'saravamu@ncat.edu', 'NSF_ID': '000572494', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}, {'FirstName': 'Patricia', 'LastName': 'Mead', 'PI_MID_INIT': 'F', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Patricia F Mead', 'EmailAddress': 'pmead@nsu.edu', 'NSF_ID': '000243399', 'StartDate': '08/05/2024', 'EndDate': None, 'RoleCode': 'Co-Principal Investigator'}]

{'Name': 'Clark Atlanta University', 'CityName': 'ATLANTA', 'ZipCode': '303144358', 'PhoneNumber': '4048806990', 'StreetAddress': '223 JAMES P BRAWLEY DR SW', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Georgia', 'StateCode': 'GA', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_ORG': 'GA05', 'ORG_UEI_NUM': 'JGA3E25MFDV9', 'ORG_LGL_BUS_NAME': 'CLARK ATLANTA UNIVERSITY, INC.', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Clark Atlanta University', 'CityName': 'ATLANTA', 'StateCode': 'GA', 'ZipCode': '303144358', 'StreetAddress': '223 JAMES P BRAWLEY DR SW', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Georgia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '05', 'CONGRESS_DISTRICT_PERF': 'GA05'}

[{'Code': '032Y00', 'Text': 'Eddie Bernice Johnson INCLUDES'}, {'Code': '159400', 'Text': 'Hist Black Colleges and Univ'}]

2024~1989315

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435570.xml'}

I-Corps: Translation Potential of a Personalized Interactive Artificial Intelligence (AI) System for Living Kidney Donor Engagement

NSF

09/01/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '15030000', 'Directorate': {'Abbreviation': 'TIP', 'LongName': 'Dir for Tech, Innovation, & Partnerships'}, 'Division': {'Abbreviation': 'TI', 'LongName': 'Translational Impacts'}}

{'SignBlockName': 'Molly Wasko', 'PO_EMAI': 'mwasko@nsf.gov', 'PO_PHON': '7032924749'}

The broader impact of this I-Corps project is based on the development of a Generative Pre-trained Transformer (GPT) system specifically designed to help potential kidney donors access personalized answers during their online information-seeking journey. This technology can help transplant centers attract more live kidney donors, which is essential for achieving superior transplant outcomes for patients. This technology could prove to be a significant cost-effective strategy for Medicare as the main payer of kidney care in the country, while enabling doctors and hospitals to achieve better outcomes for patients. The lack of comprehensive and personalized online material about kidney transplant and kidney donation has been a major barrier for potential kidney donors to complete the donation process. This project aims to lower this barrier by introducing accurate and traceable generative artificial intelligence (AI) patient support, coupled with live-donor mentors offered by transplant centers, to increase the live kidney donation rate and save more patients. <br/><br/>This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the development of a well-trained Generative Pre-trained Transformer (GPT) AI system with a comprehensive dataset encompassing all kidney transplant and donation related topics. Existing GPT models are not specialized in the field of kidney donation and this technology would change that. Online information from kidney transplant centers and other professional transplant-related organizations will create a well-trained GPT model with a comprehensive dataset. A context-aware prompts-generation (CAPG) model enables personalization of the GPT responses.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/22/2024

07/22/2024

None

Grant

47.084

1

4900

4900

2435577

{'FirstName': 'Naoru', 'LastName': 'Koizumi', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Naoru Koizumi', 'EmailAddress': 'nkoizumi@gmu.edu', 'NSF_ID': '000206493', 'StartDate': '07/22/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'ZipCode': '220304422', 'PhoneNumber': '7039932295', 'StreetAddress': '4400 UNIVERSITY DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Virginia', 'StateCode': 'VA', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'VA11', 'ORG_UEI_NUM': 'EADLFP7Z72E5', 'ORG_LGL_BUS_NAME': 'GEORGE MASON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'H4NRWLFCDF43'}

{'Name': 'George Mason University', 'CityName': 'FAIRFAX', 'StateCode': 'VA', 'ZipCode': '220304422', 'StreetAddress': '4400 UNIVERSITY DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Virginia', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'VA11'}

{'Code': '802300', 'Text': 'I-Corps'}

2024~50000

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435577.xml'}

Conference: 2024 NSF CyberTraining/SCIPE Principal Investigator (PI) Meeting

NSF

07/15/2024

06/30/2025

{'Value': 'Standard Grant'}

{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}

{'SignBlockName': 'Sharmistha Bagchi-Sen', 'PO_EMAI': 'shabagch@nsf.gov', 'PO_PHON': '7032928104'}

This project supports a two-day meeting for leaders and researchers from the National Science Foundation's (NSF) CyberTraining and SCIPE programs. The event will be held alongside the meeting for the NSF's Cyberinfrastructure for Sustained Scientific Innovation program. It will serve as a platform for participants to share information about their projects, goals, and outcomes with others, including NSF program directors. The meeting will also feature joint sessions for discussing common interests and exploring opportunities for collaboration between the two NSF programs. <br/><br/>The CyberTraining/SCIPE PI meeting aims to advance the community-building efforts of previous workshops by providing a platform for principal investigators (PIs) to share technical information about their projects with peers, NSF program directors, and other stakeholders. This forum facilitates the exploration of innovative topics within NSF workforce development communities, promotes discussions on best practices, and generates new ideas for training and educating CI researchers and professionals. The organizing committee will select speakers and panelists based on their research and expertise in CyberTraining for CI and SCIPE professionals. PIs will also provide valuable feedback on emerging opportunities and challenges, and participants will include projects identified by NSF as complementary to CyberTraining/SCIPE initiatives, fostering potential collaborations. This year's program will explore the impact of AI on the NSF research and training community. The workshop will convene leading experts from the CyberTraining/SCIPE and broader communities to discuss and share innovations and best practices in training CI and SCIPE professionals, aiming to lay the groundwork for the next generation of professionals who will support the development, deployment, and utilization of NSF resources and services. These collaborations will enhance productivity, accelerate research in science and engineering, and significantly increase the impact of NSF's output, particularly within OAC’s programs. The selection of speakers and panelists will ensure diversity and alignment with best practices for broadening STEM participation. Additionally, the organizing committee will extend invitations to relevant NSF program managers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/05/2024

07/05/2024

None

Grant

47.070

1

4900

4900

2435580

{'FirstName': 'Mary', 'LastName': 'Thomas', 'PI_MID_INIT': 'P', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Mary P Thomas', 'EmailAddress': 'mpthomas@ucsd.edu', 'NSF_ID': '000421108', 'StartDate': '07/05/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'ZipCode': '920930021', 'PhoneNumber': '8585344896', 'StreetAddress': '9500 GILMAN DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'California', 'StateCode': 'CA', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_ORG': 'CA50', 'ORG_UEI_NUM': 'UYTTZT6G9DT1', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF CALIFORNIA, SAN DIEGO', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of California-San Diego', 'CityName': 'LA JOLLA', 'StateCode': 'CA', 'ZipCode': '920930021', 'StreetAddress': '9500 GILMAN DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'California', 'CountryFlag': '1', 'CONGRESSDISTRICT': '50', 'CONGRESS_DISTRICT_PERF': 'CA50'}

{'Code': '044Y00', 'Text': 'CyberTraining - Training-based'}

2024~99998

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435580.xml'}

Collaborative Research: Frameworks: Interoperable High-Performance Classical, Machine Learning and Quantum Free Energy Methods in AMBER

NSF

07/01/2024

06/30/2027

{'Value': 'Standard Grant'}

{'Code': '05090000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'OAC', 'LongName': 'Office of Advanced Cyberinfrastructure (OAC)'}}

{'SignBlockName': 'Varun Chandola', 'PO_EMAI': 'vchandol@nsf.gov', 'PO_PHON': '7032922656'}

With support from the Office of Advanced Infrastructure and the Division of Chemistry at NSF, Professor Merz and his group will work on molecular simulation cyberinfrastructure. Molecular simulations have become an invaluable tool for research and technology development in chemical, pharmaceutical, and materials sciences. With the availability of specialized hardware such as graphics processing units (GPUs), molecular dynamics simulations using classical or molecular mechanical force fields have reached the spatial and temporal scales needed to address important real-world problems in the chemical and biological sciences. Free energy simulations are a particularly important and challenging class of molecular simulations that are critical to gain a predictive understanding of chemical processes. For example, free energy methods can predict the barrier height and rates for chemical reactions, whether a reaction will occur, or how tightly a drug binds to a target. These predictions are extremely valuable for the design of new catalytic agents or drugs. However, the predictive capability of free energy simulations is sensitive to the underlying model that describes the inter-atomic potential energy and forces. Accurate free energy simulations of chemical processes require potential energy models that capture the essential physics and can respond to changes in the chemical environment, but conventional force field models are unsuitable for many processes involving bond breaking and formation as seen, for example, in catalyst design. Consequently, there is great need to extend the scope of free energy methods by enabling the use of a broader range of potential energy models that are more accurate as well as reactive and/or capable of quantum mechanical many-body polarization and charge transfer. The cyberinfrastructure created by this project allows for the routine application of free energy methods, using quantum mechanics, machine learning, reactive and classical potentials to a myriad of important problems that advance the state-of-the art in the biological and chemical sciences. The tools can be applied by a range of scientists to address fundamental problems of national interest, for example, in the design of drugs against zoonotic diseases (e.g., COVID-19), the design of materials with novel functions and in the design of improved batteries. Given the sophistication of the methods employed, education of a diverse pool of chemical, biological and computer scientists to advance this field is essential and is addressed in this project, thereby training the next generation of computational scientists that will form the backbone of the work force of the future.<br/> <br/>The project develops accurate and efficient free energy software within a powerful new multiscale modeling framework in the AMBER suite of programs for applications in chemistry, biology, and materials science. The multiscale framework enables the design and use of new classes of mixed-method force fields that involve interoperability between several existing and emerging reactive, machine learning and quantum many-body potentials. These potentials have enhanced accuracy, robustness, and predictive capability compared to classical molecular mechanical force fields and enable the study of chemical reactions and catalysis. The cyberinfrastructure supports innovative multi-layered hybrid potentials that can be customized to meet the needs of complex applications in biotechnology development, enzyme design and drug discovery. A robust endpoint "book-ending" approach that leverages the GPU-accelerated capability of the AMBER molecular dynamics engine is used to reach these goals. Specifically, the open-source high-performance software for free energy simulations is designed for multi-layered hybrid potentials using combinations of linear-scaling many-body quantum mechanical methods via the GPU-accelerated QUICK package, scalable reactive ReaxFF force fields via the PuReMD package, as well as the recently developed DeepMD-SE, ANAKIN-ME (ANI) and AP-Net families of machine learning potentials. The cyberinfrastructure is built upon the existing high-performance CUDA MD engine in AMBER and extends it to a broad range of GPU-accelerated architectures using industry-standard programming models. Scalability is ensured using innovative parallel algorithms. High impact is achieved by leveraging AMBER's broad user base to expand the scope and success of FE applications. In this way, the project leverages existing recognized capabilities and actively engages a diverse team of collaborators and the broader molecular simulations community. The cyberinfrastructure delivered by the project enables a wide range of new and enhanced applications for a broad community of users in academia, industry, and national laboratories. These applications include drug discovery, enzyme catalysis, and biomaterials design. The AMBER suite of programs has a long-standing extensive worldwide userbase, and is widely used on national production cyberinfrastructure. The enhancement of AMBER as an established, proven sustainable, and widely used package will ensure that the software has a broad impact well beyond the end of the project. The project will also train a diverse population of students and researchers in theory, programming, computational chemistry/biology, computer science, scientific writing, and communication.<br/><br/>This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Chemistry within the NSF Directorate for Mathematical and Physical Sciences.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/03/2024

07/03/2024

None

Grant

47.049, 47.070

1

4900

4900

2435622

{'FirstName': 'Kenneth', 'LastName': 'Merz', 'PI_MID_INIT': 'M', 'PI_SUFX_NAME': 'Jr', 'PI_FULL_NAME': 'Kenneth M Merz', 'EmailAddress': 'merzk@ccf.org', 'NSF_ID': '000214779', 'StartDate': '07/03/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Cleveland Clinic Foundation', 'CityName': 'CLEVELAND', 'ZipCode': '441950001', 'PhoneNumber': '2164456440', 'StreetAddress': '9500 EUCLID AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Ohio', 'StateCode': 'OH', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_ORG': 'OH11', 'ORG_UEI_NUM': 'TDGUJ1WA4UJ9', 'ORG_LGL_BUS_NAME': 'THE CLEVELAND CLINIC FOUNDATION', 'ORG_PRNT_UEI_NUM': 'TDGUJ1WA4UJ9'}

{'Name': 'Cleveland Clinic Foundation', 'CityName': 'CLEVELAND', 'StateCode': 'OH', 'ZipCode': '441950001', 'StreetAddress': '9500 EUCLID AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Ohio', 'CountryFlag': '1', 'CONGRESSDISTRICT': '11', 'CONGRESS_DISTRICT_PERF': 'OH11'}

{'Code': '800400', 'Text': 'Software Institutes'}

2022~1811050

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435622.xml'}

Collaborative Research: EAGER: Non-Antiperiodic Nonlinear Electrophoresis (NANEP) of Colloidal Particles

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Shahab Shojaei-Zadeh', 'PO_EMAI': 'sshojaei@nsf.gov', 'PO_PHON': '7032928045'}

Electrically charged objects move when exposed to an electric field: this phenomenon is termed electrophoresis. Most research in this field has focused on electrophoretic motion in small-amplitude electric fields, where the velocity of the object is linearly proportional to the magnitude of the electric field. In contrast, this project will quantify the nonlinear electrophoretic motion of microscopic-sized charged particles immersed in an electrolyte solution under a large-amplitude field. A novel technique called Non-Antiperiodic Nonlinear Electrophoresis (NANEP) is proposed to enable net electrophoretic motion of such particles under an alternating (ac) field. Experimental measurements and computational modeling will be employed to provide proof-of-concept for NANEP. The ability to affect net electrophoretic particle movement through NANEP could lead to new methods for hierarchical assembly of particles. Further, it is envisioned that NANEP will provide the scientific foundation for new separation schemes for biomolecules in lab-on-a-chip microfluidic devices. The project will also have broader educational impacts including course development, undergraduate research experiences, and outreach activities.<br/><br/>The project will quantify the Non-Antiperiodic Nonlinear Electrophoresis (NANEP) of micro-scale colloidal particles via experiments and computations. The first objective is to predict NANEP via numerical solution of the nonlinear electrokinetic equations governing fluid flow, ion transport, and electrostatic fields in electrophoresis. The numerical scheme will employ a custom spectral element code with adaptive time stepping, which will enable efficient, accurate computation of NANEP across a wide range of the experimentally relevant parameter space. The aim is to determine which regions of this space result in the maximum net particle movement under NANEP. The second objective is to experimentally measure electrophoretic particle migration during NANEP. This will be accomplished by observing particle motion in a microfluidic channel under a non-antiperiodic field. Importantly, the results from these two objectives can be directly compared in an essentially parameter-free manner. The proposed research will provide the first computational predictions and experimental measurements for NANEP of colloidal particles.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/01/2024

08/01/2024

None

Grant

47.041

1

4900

4900

2435631

{'FirstName': 'Aditya', 'LastName': 'Khair', 'PI_MID_INIT': None, 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Aditya Khair', 'EmailAddress': 'akhair@andrew.cmu.edu', 'NSF_ID': '000572369', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Carnegie-Mellon University', 'CityName': 'PITTSBURGH', 'ZipCode': '152133815', 'PhoneNumber': '4122688746', 'StreetAddress': '5000 FORBES AVE', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'StateCode': 'PA', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_ORG': 'PA12', 'ORG_UEI_NUM': 'U3NKNFLNQ613', 'ORG_LGL_BUS_NAME': 'CARNEGIE MELLON UNIVERSITY', 'ORG_PRNT_UEI_NUM': 'U3NKNFLNQ613'}

{'Name': 'Carnegie Mellon University', 'CityName': 'PITTSBURGH', 'StateCode': 'PA', 'ZipCode': '152133815', 'StreetAddress': '5000 FORBES AVE', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Pennsylvania', 'CountryFlag': '1', 'CONGRESSDISTRICT': '12', 'CONGRESS_DISTRICT_PERF': 'PA12'}

{'Code': '141500', 'Text': 'PMP-Particul&MultiphaseProcess'}

2024~169200

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435631.xml'}

Collaborative Research: EAGER: Non-Antiperiodic Nonlinear Electrophoresis (NANEP) of Colloidal Particles

NSF

09/01/2024

08/31/2026

{'Value': 'Standard Grant'}

{'Code': '07020000', 'Directorate': {'Abbreviation': 'ENG', 'LongName': 'Directorate For Engineering'}, 'Division': {'Abbreviation': 'CBET', 'LongName': 'Div Of Chem, Bioeng, Env, & Transp Sys'}}

{'SignBlockName': 'Shahab Shojaei-Zadeh', 'PO_EMAI': 'sshojaei@nsf.gov', 'PO_PHON': '7032928045'}

Electrically charged objects move when exposed to an electric field: this phenomenon is termed electrophoresis. Most research in this field has focused on electrophoretic motion in small-amplitude electric fields, where the velocity of the object is linearly proportional to the magnitude of the electric field. In contrast, this project will quantify the nonlinear electrophoretic motion of microscopic-sized charged particles immersed in an electrolyte solution under a large-amplitude field. A novel technique called Non-Antiperiodic Nonlinear Electrophoresis (NANEP) is proposed to enable net electrophoretic motion of such particles under an alternating (ac) field. Experimental measurements and computational modeling will be employed to provide proof-of-concept for NANEP. The ability to affect net electrophoretic particle movement through NANEP could lead to new methods for hierarchical assembly of particles. Further, it is envisioned that NANEP will provide the scientific foundation for new separation schemes for biomolecules in lab-on-a-chip microfluidic devices. The project will also have broader educational impacts including course development, undergraduate research experiences, and outreach activities.<br/><br/>The project will quantify the Non-Antiperiodic Nonlinear Electrophoresis (NANEP) of micro-scale colloidal particles via experiments and computations. The first objective is to predict NANEP via numerical solution of the nonlinear electrokinetic equations governing fluid flow, ion transport, and electrostatic fields in electrophoresis. The numerical scheme will employ a custom spectral element code with adaptive time stepping, which will enable efficient, accurate computation of NANEP across a wide range of the experimentally relevant parameter space. The aim is to determine which regions of this space result in the maximum net particle movement under NANEP. The second objective is to experimentally measure electrophoretic particle migration during NANEP. This will be accomplished by observing particle motion in a microfluidic channel under a non-antiperiodic field. Importantly, the results from these two objectives can be directly compared in an essentially parameter-free manner. The proposed research will provide the first computational predictions and experimental measurements for NANEP of colloidal particles.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/01/2024

08/01/2024

None

Grant

47.041

1

4900

4900

2435632

{'FirstName': 'Blanca', 'LastName': 'Lapizco-Encinas', 'PI_MID_INIT': 'H', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Blanca H Lapizco-Encinas', 'EmailAddress': 'bhlbme@rit.edu', 'NSF_ID': '000624555', 'StartDate': '08/01/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'ZipCode': '146235603', 'PhoneNumber': '5854757987', 'StreetAddress': '1 LOMB MEMORIAL DR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'New York', 'StateCode': 'NY', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_ORG': 'NY25', 'ORG_UEI_NUM': 'J6TWTRKC1X14', 'ORG_LGL_BUS_NAME': 'ROCHESTER INSTITUTE OF TECHNOLOGY', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'Rochester Institute of Tech', 'CityName': 'ROCHESTER', 'StateCode': 'NY', 'ZipCode': '146235603', 'StreetAddress': '1 LOMB MEMORIAL DR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'New York', 'CountryFlag': '1', 'CONGRESSDISTRICT': '25', 'CONGRESS_DISTRICT_PERF': 'NY25'}

{'Code': '141500', 'Text': 'PMP-Particul&MultiphaseProcess'}

2024~129750

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435632.xml'}

Collaborative Research: NCS: FO: Enhancing Episodic Memory through Real-world Integration of Brain Recording and Stimulation with Semantic Alignment of Human and IoT Perception

NSF

06/15/2024

08/31/2025

{'Value': 'Standard Grant'}

{'Code': '05020000', 'Directorate': {'Abbreviation': 'CSE', 'LongName': 'Direct For Computer & Info Scie & Enginr'}, 'Division': {'Abbreviation': 'IIS', 'LongName': 'Div Of Information & Intelligent Systems'}}

{'SignBlockName': 'Kenneth Whang', 'PO_EMAI': 'kwhang@nsf.gov', 'PO_PHON': '7032925149'}

The goal of this project is to build and evaluate a system for exploring how the human brain processes information in everyday real-world environments. The investigators will directly record from the brain while participants navigate the real world, while synchronously recording information about the participant's first-person experience from a set of sensors including cameras, microphones, eye-tracking, and physiological recordings. Neurosurgical participants with a clinically implanted neural recording and stimulation system volunteer for these experiments, providing rare direct human brain recordings as they move around a real-world environment. The rich sensor data captured from the participant's first-person experience will be analyzed in relation to the neural data to infer how changes in patterns of neural activity over time relate to changes in experience. In addition, stimulation will be applied, at safe levels and timed according to "event boundaries" of the participant's experience, to determine whether memories of specific events can be enhanced. The proposed platform that allows for neural recording, direct brain stimulation, and synchronization with external, wearable devices will open an entirely new area of research at the intersection of computer science, engineering, cognition, and clinical neuroscience. These studies will launch and accelerate an emerging and pivotal area of research that will provide therapeutic interventions, proven in the real-world, for participants afflicted with debilitating cognitive disorders. This project will also make substantial contributions to education and outreach, including the development of K-12 classroom modules, interdisciplinary graduate training, outreach to industry partners in the neuromodulation field, and workshops at local Salt Lake City memory care communities.<br/><br/>Development of this neural and first-person experience recording system will entail three collaborative research tasks: i) Synchronizing the Human Experience Relative to Neuronal Events: This module will develop a robust framework to record and synchronize neuronal activity along with internet of things (IoT) sensor data representing a broad subset of human sensory channels. The design will be portable such that the human experience can be reasoned about outside of a simulated lab environment. ii) Real-time Semantic Alignment between Human and IoT Perception: Reasoning about the complex relationships between neural biomarkers and the human experience captured by IoT sensing requires more than sensor synchronization. Neural-symbolic approaches that integrate the perception capabilities of deep learning with human logic will be leveraged to reason about the high-level complex spatiotemporal dependencies across a heterogeneous set of sensors. iii) Enhancing Episodic Memories of Real-world Experiences with DBS: Given a proper characterization of neural oscillations associated with event boundaries, the investigators will work to enhance episodic memories of real-world experiences with wireless deep brain stimulation (DBS) devices by directly stimulating the human brain. Under medical supervision, stimulation will be applied to the human amygdala at and between event boundaries in subjects with implanted stimulation devices as they encounter novel, 3D augmented reality objects while navigating a large-scale, real-world environment. Memory will be subsequently tested in laboratory and real-world settings. These three research areas will develop a situational understanding of neuronal activity in the context of human experience. They will further lay the foundation for future research directions in safe and effective stimulation of the brain in response to human experience in the wild.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

07/02/2024

07/02/2024

None

Grant

47.070, 47.076

1

4900

4900

2435642

{'FirstName': 'Luis', 'LastName': 'Garcia', 'PI_MID_INIT': 'A', 'PI_SUFX_NAME': None, 'PI_FULL_NAME': 'Luis A Garcia', 'EmailAddress': 'la.garcia@utah.edu', 'NSF_ID': '000827362', 'StartDate': '07/02/2024', 'EndDate': None, 'RoleCode': 'Principal Investigator'}

{'Name': 'University of Utah', 'CityName': 'SALT LAKE CITY', 'ZipCode': '841129049', 'PhoneNumber': '8015816903', 'StreetAddress': '201 PRESIDENTS CIR', 'StreetAddress2': None, 'CountryName': 'United States', 'StateName': 'Utah', 'StateCode': 'UT', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_ORG': 'UT01', 'ORG_UEI_NUM': 'LL8GLEVH6MG3', 'ORG_LGL_BUS_NAME': 'UNIVERSITY OF UTAH', 'ORG_PRNT_UEI_NUM': None}

{'Name': 'University of Utah', 'CityName': 'SALT LAKE CITY', 'StateCode': 'UT', 'ZipCode': '841129049', 'StreetAddress': '201 PRESIDENTS CIR', 'CountryCode': 'US', 'CountryName': 'United States', 'StateName': 'Utah', 'CountryFlag': '1', 'CONGRESSDISTRICT': '01', 'CONGRESS_DISTRICT_PERF': 'UT01'}

[{'Code': '798000', 'Text': 'ECR-EDU Core Research'}, {'Code': '862400', 'Text': 'IntgStrat Undst Neurl&Cogn Sys'}]

2021~267980

{'url': 'https://www.nsf.gov/awardsearch/download?DownloadFileName=2024&All=true', 'xml': '2435642.xml'}

Conference: Object Perception, Attention, and Memory meeting

NSF

09/01/2024

08/31/2027

{'Value': 'Standard Grant'}

{'Code': '04040000', 'Directorate': {'Abbreviation': 'SBE', 'LongName': 'Direct For Social, Behav & Economic Scie'}, 'Division': {'Abbreviation': 'BCS', 'LongName': 'Division Of Behavioral and Cognitive Sci'}}

{'SignBlockName': 'Betty Tuller', 'PO_EMAI': 'btuller@nsf.gov', 'PO_PHON': '7032927238'}

Our daily functioning relies on our ability to recognize objects, control our attention, and encode events in memory, although much is still unknown about these critical mental processes. The Object Perception, Attention, and Memory (OPAM) conference is a nationally-recognized venue for early-career scientists to present cutting-edge research on these very topics, employing a variety of experimental techniques such as behavioral methods, neuroimaging, computational modeling, animal models, and more. Research on these cognitive processes is essential for developing a better understanding of the human mind and brain, and the OPAM conference has over 30 years of history as a leader in this area. The current project aims to amplify OPAM's impact on the field by broadening who is participating in the meeting, by providing critical networking and career guidance, and by offering easily-accessible professional training. All of these initiatives are free of charge to the scientific community, and help prepare early-career scientists to study these important topics effectively in the future.<br/><br/>The OPAM conference is held as an affiliate meeting of the Psychonomic Society’s annual conference. The current project increases financial support available for conference presenters, particularly to reach the "missing millions" in STEM. Principal Investigators and conference organizers also engage in a series of outreach efforts to narrow the gap between the demographics of the research community at OPAM and in the cognitive sciences more broadly and the demographics of the whole nation. A new keynote speaker format has been adopted in which the speaker shares experiences from their early-career stage that will inspire and guide other early-career researchers. A “Lunch with an Expert” event allows attendees to learn about scientific topics and receive career guidance from established experts in a friendly setting. Outside of the conference itself, OPAM hosts online workshops throughout the year, focusing on topics critical to the professional development and technical skill-building of early-career researchers.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

08/20/2024

08/20/2024

None

Grant

47.075