Project Grant 2523438
- This $405,917 Project Grant was awarded on October 1, 2025 by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The grant establishes a framework for securely sharing sensitive medical video data, such as footage of tracheostomy-dependent children, between healthcare providers in a privacy-preserving manner. The project brings together advanced technologies like face identification, video pixelation, and...
- This $193,885 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a privacy-preserving framework for sharing and learning from scarce medical data, specifically focused on videos of tracheostomy-dependent children. The 3-year project, running from October 1, 2025 to September 30, 2028, will establish a comprehensive suite of privacy mechanisms to enable the secure sharing of sensitive video...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) provides $129,032.00 to develop methods for auditing and certifying the privacy guarantees of machine learning models trained on sensitive patient data. The research aims to create techniques that allow organizations to safely share these models without compromising individual privacy, in order to advance medical research and scientific discovery, enhance healthcare...
- This $540,000 federal Project Grant award was made by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) on June 15, 2025 to Emory University. The project, titled "SATC: CORE: SMALL: TOWARD ADVERSARIALLY ROBUST AND PRIVACY-PRESERVING EHR SYSTEMS: DATA COMPLEXITY AND NEW TRAINING PARADIGMS," aims to address adversarial robustness and privacy concerns in modern electronic health record (EHR) systems....
- This $150,000 Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) to Vanderbilt University Medical Center supports the development of methods to enable the safe sharing of machine learning models trained on sensitive healthcare data without compromising individual privacy. The key objectives are to evaluate the privacy properties of shared models, develop techniques for auditing and certifying their privacy guarantees, and provide...
- This Project Grant award from the National Science Foundation (CFDA 47.084 - NSF Technology, Innovation, and Partnerships) to Virginia Polytechnic Institute & State University supports the development of methods to allow organizations to safely share machine learning models trained on sensitive patient data without compromising individual privacy. The $128,985 project, running from October 2025 to September 2028, aims to create new techniques for auditing models, certifying their privacy...
- This $124,786 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to develop techniques to allow organizations to participate in the creation of privacy-preserving synthetic data without revealing their real data. The project, led by the University of Central Florida in partnership with the University of Washington Tacoma, will advance the state-of-the-art in secure multiparty computation and fully...
- 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 $590,731 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) federal grant program (CFDA 47.070). The grant was awarded to Wichita State University to conduct research on detecting and reducing unauthorized personal data collection in mobile applications and their backend servers. The project aims to develop novel techniques to compute the minimum personal information required for app...
- This National Science Foundation (NSF) Project Grant award, under the CFDA 47.070 Computer and Information Science and Engineering program, provides $250,000 in funding to Arizona State University to develop intelligent anonymization methods for preserving the privacy of clients' bio-signals while retaining data utility for clinical purposes. The key products and services delivered through this 3-year award (10/1/2024 - 9/30/2027) include: 1) Designing reinforcement learning-guided generative...
This federal Project Grant award of $599,040.00 was provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to Kansas State University. The project, titled "COLLABORATIVE RESEARCH: SATC 2.0: RES: A PRIVACY-PRESERVING FRAMEWORK FOR SHARING AND LEARNING FROM SCARCE MEDICAL DATA", aims to establish a framework for securely sharing sensitive medical data, such as videos of tracheostomy-dependent children, between healthcare providers while preserving patient privacy. The research will leverage advanced technologies, including face identification, video pixelation, and AI-driven text-to-video generation, to develop a unified system that enables the safe use of this scarce medical data for training monitoring systems. The project runs from October 1, 2025 to September 30, 2028 and has the potential for broader applications in fields requiring video supervision of human subjects.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $599.0k | 8/19/25 |