Project Grant 2613735
- This $538,133 Project Grant, awarded by the National Science Foundation's (NSF) Division of Computer and Network Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070), funds research on privacy-preserving statistical analysis of continuously generated sensitive data. The project, which runs from August 1, 2025 through July 31, 2028 and is performed at Rutgers University's Newark campus, develops novel algorithms that enable robust differential privacy...
- The National Science Foundation Division of Computer and Network Systems awarded Massachusetts Institute of Technology $417,261 on January 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to conduct empirical research on the downstream implications of privacy-preserving analytics development and deployment. The project investigates the organizational, managerial, and real-world impacts of mathematical and statistical techniques—including differential...
- The National Science Foundation Division of Computer and Network Systems awarded Texas Tech University $344,417 on July 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to conduct research on differential privacy and random geometry. The project interprets differential privacy through random geometry, random matrix methods, concentration of measure, and learning theory. It represents privacy mechanisms based on noise perturbation through geometric objects...
- This three-year Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering federal grant program (CFDA 47.070), provides $299,619 to the University of Virginia to lay the foundations for differentially private Internet measurement. Specifically, the award supports three main research thrusts. The first will study existing privacy issues in collecting and sharing Internet measurement data and develop an...
- The National Science Foundation Division of Computer and Network Systems awarded the University of Virginia $395,277 on October 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for a CAREER project advancing differentially private data synthesis. The research develops methods to create synthetic datasets that preserve useful patterns from sensitive data while protecting individual privacy, enabling hospitals, companies, public agencies, and researchers to...
- This $175,000 two-year Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of novel local differential privacy techniques to significantly improve the privacy-utility tradeoff in multi-attribute data analysis. The Rochester Institute of Technology will develop techniques exploiting correlation in multi-attribute data and correlated random...
- 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 $599,994 Project Grant award was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) to the University of Vermont & State Agricultural College. The grant supports a 3-year project to design a standardized "Differential Privacy Certificate" (DP Certificate) that can effectively and accountably communicate the actual privacy protections of differential privacy techniques to audiences with...
- The National Science Foundation Division of Computer and Network Systems awarded the University of Alabama $310,043 on January 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop differential privacy mechanisms implemented directly on embedded memories to protect data privacy in electronic devices. The research addresses a gap in existing differential privacy studies by realizing privacy protections at the memory hardware level rather than through...
- The National Science Foundation Division of Computer and Network Systems awarded Arizona State University $391,490 on May 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to model and mitigate privacy risks to student data at higher education institutions. The project formalizes privacy risk modeling processes at universities and creates a threat ontology. It develops two classes of mitigation techniques: one based on censoring internal representations of...
The National Science Foundation Division of Computer and Network Systems awarded Georgetown University $550,000 on October 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop formal privacy models that extend differential privacy beyond worst-case guarantees and address the utility-privacy gap in modern data analysis. The project develops privacy-preserving data analysis paradigms intended for use by researchers, industry, and regulators. Research activities focus on preventing specific privacy vulnerabilities—reconstruction and singling-out attacks—when differential privacy creates prohibitive utility costs. The team designs novel algorithmic approaches including trust settings that leverage public pre-training data and conditional utility under realistic data distributions to expand the utility frontier of standard differential privacy. The project trains doctoral students and postdoctoral fellows, integrates findings into academic curricula, and disseminates research materials publicly. Performance runs from October 1, 2026, through September 30, 2030, at Georgetown University in Washington, DC 20057.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $550.0k | 8/4/26 |