This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $279,959 to Carnegie Mellon University to advance the frontiers of differential privacy algorithms for private learning and synthetic data generation. The 5-year research project aims to develop a theoretical framework to better capture practical privacy scenarios, design practical privacy-preserving algorithms, and create auditing...
The National Science Foundation (NSF) awarded a $387,044 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to Arizona State University to improve the fundamental limits of privacy-enhancing technologies (PETs). The research aims to develop new PET methods that optimize the balance between preserving individual privacy and enabling comprehensive data analysis for societal benefit in domains such as healthcare, education, and resource allocation. Key...
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 Division of Computer and Network Systems awarded a $115,995 Project Grant to Carnegie Mellon University for research titled "COLLABORATIVE RESEARCH: SATC: CORE: SMALL: FOUNDATIONS FOR THE NEXT GENERATION OF PRIVATE LEARNING SYSTEMS." The place of performance is Pittsburgh, Pennsylvania. This award will support research from October 1, 2021 to September 30, 2022 under the NSF's Computer and Information Science and Engineering program (CFDA #47.070). The...
The National Science Foundation (NSF) awarded a $423,204 Project Grant under the Computer and Information Science and Engineering (CISE) program to The Pennsylvania State University (Penn State) for a 4-year collaborative research project titled "COLLABORATIVE RESEARCH: SATC: CORE: MEDIUM: DIFFERENTIALLY PRIVATE SQL WITH FLEXIBLE PRIVACY MODELING, MACHINE-CHECKED SYSTEM DESIGN, AND ACCURACY OPTIMIZATION." The goal is to develop an open-source, customizable system for preserving privacy...
This three-year, $110,645 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), supports research into the implementation of privacy in software systems by software developers. The Stanford University research team will examine discussions among developers in response to new privacy regulations and laws, related code updates in public repositories, and developer reactions to...
This Project Grant award from the National Science Foundation's Division of Computing and Communication Foundations, under CFDA Program 47.070 "Computer and Information Science and Engineering", provides $225,441 to Harvard University to research fundamental limits of privacy-enhancing technologies. The goal is to develop new methods that optimize privacy-preserving techniques while minimizing distortion and bias, in order to enable more accurate, fair, and privacy-protected machine...
Carnegie Mellon University was awarded a $350,000 project grant from the National Science Foundation for the period of April 1, 2021 through March 31, 2024. The grant was awarded under the NSF's Computer and Information Science and Engineering program, which supports investigator-initiated research and education in all areas of computing, communications, and information science and engineering. Specifically, the grant will fund research into foundations and constructions for securely executing...
The National Science Foundation (NSF) awarded a $179,055 Project Grant to the University of Virginia under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports collaborative research to develop privacy-preserving algorithms for fundamental problems in graph mining and network science. The project aims to create scalable, accurate graph differential privacy algorithms for applications like healthcare, social networks, finance, and computational...
This National Science Foundation project grant of $300,000 will fund foundational research on differentially private Internet measurement from October 2022 to September 2025. Under the Computer and Information Science and Engineering program, researchers at the University of California Irvine will conduct three thrusts of work to lay the groundwork for deploying differential privacy in processing Internet measurement data. Specifically, Thrust 1 will study existing practices for collecting and...