CAREER: Advancing Differentially Private Data Synthesis: A Holistic Approach — NSF Award to University of Virginia Main Campus (VA
This project studies how to create synthetic datasets that retain useful patterns from sensitive data while protecting privacy of individuals. Many hospitals, companies, public agencies, and researchers need data to improve services, test ideas, etc., but they often cannot share original records because they contain pr
| Award title | CAREER: Advancing Differentially Private Data Synthesis: A Holistic Approach |
|---|---|
| Award ID | 2543284 |
| Awardee | University of Virginia Main Campus |
| City | CHARLOTTESVILLE |
| State | VA |
| Amount obligated | $395,277 |
| Principal investigator | Tianhao Wang |
| Program | Secure &Trustworthy Cyberspace |
| Start date | 10/01/2026 |
| Abstract | This project studies how to create synthetic datasets that retain useful patterns from sensitive data while protecting privacy of individuals. Many hospitals, companies, public agencies, and researchers need data to improve services, test ideas, etc., but they often cannot share original records because they contain private information. This project addresses this gap by making data sharing safer and more useful. The project's novelties are creating a general way to break synthetic data generati |
| Source | NSF Awards |
$799/mo
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