Project Grant 2500961
- 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...
- 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 $173,754 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop an innovative privacy-preserving federated learning (FL) framework suitable for heterogeneous edge devices. The key objectives are to: 1) enable tailored device-specific models to mitigate biases and enhance performance across diverse computational capabilities and data distributions, 2) utilize differential privacy...
- The National Science Foundation (NSF) awarded a $400,000 Project Grant under its Computer and Information Science and Engineering (CISE) program to Georgia Tech Research Corporation, doing business as the Office of Sponsored Programs. The grant supports a 4-year collaborative research project to develop innovative, privacy-preserving machine learning algorithms for analyzing graph-structured data. Key objectives include designing non-uniform privatization protocols to balance data utility and...
- This $350,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of advanced, privacy-preserving generative AI models for anonymizing biometric signals. The project aims to create modular and scalable anonymization methods suitable for both clinical and wearable device bio-signals, which can be customized for diverse demographics and health conditions. This will help preserve...
- This $13,843 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will fund research to develop new computer systems that allow organizations to gain insights from large datasets while keeping individual information completely private. The key research objectives are to: 1) develop new protocols for privacy-preserving data collection that enable servers to compute aggregate statistics over client data without...
- This Project Grant award from the National Science Foundation's (NSF) Technology, Innovation, and Partnerships (CFDA 47.084) program provides $128,985.00 to Virginia Polytechnic Institute & State University to develop methods for auditing and certifying the privacy guarantees of machine learning (ML) models trained on sensitive patient data. The goal is to enable secure sharing of these models to advance medical research and scientific discovery, while protecting personal privacy rights. The...
- This five-year, $997,720 Project Grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop new mathematical models and algorithms for genetic data analysis using deep learning techniques. Funded through the NSF's statutory mission to support basic research, the award will support research at Cornell University from July 2022 through June 2027. Specifically, the principal investigator will create novel deep generative models to replace...
- 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 $138,428 project grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) will support the development of computationally tractable structured hierarchical models to identify complex genetic associations hidden from current methods. The grantee, J. David Gladstone Institutes, will analyze genomic and clinical trait data using machine learning to build predictive models for individualized disease risk assessment and personalized...
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 realizing the full scientific potential of large-scale genomic datasets like spatially resolved transcriptomics. By leveraging federated learning techniques, the project seeks to facilitate collaborative analysis of sensitive genomic data while addressing key privacy and regulatory challenges associated with centralized data sharing. The research outputs could significantly advance the reliability, reproducibility, and insight generation from integrated genomic research across multiple institutions.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $420.0k | 7/23/25 |