Project Grant 2523407
Award Date 10/1/25
Completion Date 9/30/27
Dollars Obligated $125K
Funding Federal Agency
Awarding Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Alafaya, FL 32816, USA
Similar Awards
- This Project Grant award, provided by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070), aims to develop techniques for generating privacy-preserving synthetic data. The $274,847 award, spanning from October 1, 2025 to September 30, 2027, is a collaborative research effort between the University of Washington Tacoma and the University of Central Florida. The project seeks to advance the state-of-the-art in secure multi-party...
- This $209,368 federal Project Grant award from the National Science Foundation's Integrative Activities program (CFDA 47.083) aims to develop trusted, low-overhead tools that enable computation directly on encrypted data. The goal is to accelerate the creation of new capabilities that allow confidential data to be shared with untrusted parties who can extract insights without accessing the unencrypted data. This would increase public trust in modern AI tools and enable data-powered, socially...
- 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...
- This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) aims to develop a database architecture that integrates privacy regulations and compliance processes, enhances federated machine learning with decentralized data management functions, and automates privacy-model configuration in artificial intelligence workflows. The $249,998 award to Arizona State University will be used to address the...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $115,643.00 to develop FLTEST, an interdisciplinary testbed to automate privacy and robustness evaluations in federated learning systems. The project aims to address gaps in existing tools by developing automated test orchestration frameworks, implementing privacy attack simulation models, creating configuration vulnerability detection systems, and building...
- The National Science Foundation awarded a $600,000 Project Grant to the Trustees of Boston University under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The three-year award will support research into developing new differentially private stochastic optimization algorithms for training neural networks while preserving individual privacy. Specifically, the grantee will investigate fundamental tradeoffs between privacy and performance in modern...
- This $299,993 National Science Foundation project grant supports research under the Computer and Information Science and Engineering program (CFDA 47.070) to develop privacy-preserving models leveraging mobility data for public health purposes. The award was made to Florida A&M University on January 1, 2022 for work concluding December 31, 2023. A sub-award of $TBD was also provided to the University of West Florida to support this research. Through this funding, the awardees will deliver...
- This federal Project Grant award for $600,000.00 was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award will fund research at the University of Washington (UW) to develop new privacy-preserving authentication techniques that limit the collection of personally identifiable information, a major challenge in digital applications. The project aims to advance the theory of blind signatures and anonymous...
- This $240,062 project grant, awarded by the National Science Foundation (NSF) through its Computer and Information Science and Engineering (CISE) Program (CFDA 47.070), aims to develop efficient and scalable hardware architectures for privacy-preserving neural network inference based on ciphertext-ciphertext fully homomorphic encryption (FHE). The research will focus on designing optimized hardware building blocks, such as polynomial multipliers, and a reconfigurable FHE architecture that...
- This federal Project Grant award for $599,725 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a system for verifiable fully homomorphic encryption (FHE). The project aims to advance privacy-preserving data sharing and analysis by enabling computations on encrypted data without decryption, while also ensuring integrity and verifiability. Key research thrusts include designing near-zero-cost verifiable...