Project Grant 2500960
- This $420,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports collaborative research by Northeastern University to develop methods for protecting privacy and promoting fairness in advanced genomic research using federated learning approaches. The research aims to enable secure integration of multi-cohort genomic and genetic datasets from different institutions, which is critical for...
- This National Science Foundation (NSF) Project Grant award under the Mathematical and Physical Sciences program (CFDA 47.049) provides $250,000 to The Trustees of the University of Pennsylvania to develop advanced statistical methods for integrating and analyzing large-scale data from multiple sources, such as electronic health records and genomics data. The project aims to devise new data-driven algorithms with theoretical optimality guarantees for transfer learning, as well as adversarially...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) will support research by Vanderbilt University Medical Center (VUMC) to develop methods for auditing and certifying the privacy guarantees of machine learning models trained on sensitive patient data. The $150,000 project, running from October 1, 2025 to September 30, 2028, aims to address the challenge of safely sharing such models to advance medical research and scientific...
- This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program aims to address theoretical challenges in high-dimensional probability, with a focus on applications in data science. The $239,966 award, made on July 15, 2025, will support research to develop rigorous mathematical frameworks for understanding the authenticity and privacy of synthetic data, as well as advancing non-spectral random matrix theory....
- This $400,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports the development of secure methods to enable researchers to analyze their genetic data using controlled-access reference datasets without compromising data privacy. The project, titled "Confidential Genome Imputation and Analytics (COGIA)," aims to create secure algorithms and deployment-ready software for genome analysis in trusted...
- This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, supports research to develop improved methods for assessing privacy risks in machine learning (ML) models trained on sensitive tabular data such as patient records or financial information. The $379,224 award to The Pennsylvania State University aims to create frameworks for auditing attribute inference risks and disparities in both...
- The National Science Foundation (NSF) awarded a $400,000 Project Grant under the Computer and Information Science and Engineering (CFDA #47.070) program to the University of Illinois for a 4-year collaborative research project on privacy-preserving machine learning on graph-structured data. The project aims to develop innovative, efficient algorithms for training and updating large-scale graph neural network models while preserving the privacy of sensitive graph data across applications in areas...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) supports the development of FLTEST, an interdisciplinary testbed that automates privacy and robustness evaluations in federated learning systems. The $115,643 award, effective from October 1, 2025 through September 30, 2028, is aimed at creating standardized assessment tools to improve the reliability, validation, and trust in privacy-preserving artificial intelligence...
- The National Science Foundation (NSF) awarded a $490,133 Project Grant under the Computer and Information Science and Engineering (CISE) program to the FPF Education and Innovation Foundation. This three-year grant, commencing on July 1, 2024, supports the establishment of a Research Coordination Network (RCN) for Privacy Preserving Data Sharing and Analytics. The RCN is bringing together experts from academia, industry, and government to address challenges in developing, deploying, and...
- This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program, CFDA #47.070, provides $265,054 to Weill Medical College of Cornell University to develop a consolidated framework for computational privacy and machine learning from October 1, 2022 to September 30, 2026. The framework aims to comprehensively consider optimal tradeoffs between privacy protections and critical machine learning properties like predictive utility, fairness, and...
This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences Program (CFDA 47.049) is for a collaborative research project to develop methods to protect privacy and promote fairness in advanced genomic research using federated learning. The $250,000 award supports research to enable the integration of multi-cohort genomic and genetic datasets from different institutions, while addressing privacy and regulatory challenges associated with centralized data sharing. The project aims to develop computational approaches that allow researchers to jointly analyze data from multiple sources, detect reproducible molecular patterns, and uncover new insights without compromising individual privacy. The award will fund research at Brown University from August 1, 2025 through July 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $330.0k | 7/23/25 |