This $105,573 National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) program supports research on evaluation codes and their applications in areas such as communications, data storage, and quantum error correction. The research team at Virginia Polytechnic Institute & State University (Virginia Tech) will focus on designing evaluation codes and algorithms that utilize less information for error recovery and correction,...
The University of Virginia received a $374,876 project grant award from the National Science Foundation to conduct research titled "COLLABORATIVE RESEARCH: DASS: ACCOUNTABLE SOFTWARE SYSTEMS FOR SAFETY-CRITICAL APPLICATIONS" from October 1, 2021 through September 30, 2024. The grant was awarded under the NSF's Computer and Information Science and Engineering program (CFDA #47.070), which supports investigator-initiated research and education in all areas of computing, communications,...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop efficient error-correcting codes for improving the reliability and performance of flash memory systems, communication systems, and magnetic recording systems. The key objectives are to design linear and cyclic codes over integers modulo M using elementary symmetric functions, as well as insertion/deletion...
The University of Virginia received a $260,242 project grant award from the National Science Foundation Office of Advanced Cyberinfrastructure on January 1, 2022 to support the "EAGER: SCIDATBENCH: PRINCIPLES AND PROTOTYPES OF SCIENCE DATA BENCHMARKS" project through October 31, 2022. The grant was awarded under the Computer and Information Science and Engineering program (CFDA #47.070), which supports investigator-initiated research and education in computing, communications, and...
The University of Virginia received a $498,460 project grant award from the National Science Foundation on October 1, 2021 to support research titled "SHF: SMALL: DISTRIBUTION-AWARE TESTING FOR NEURAL NETWORKS." The project aims to develop testing techniques for neural networks that account for data distribution properties and will be completed by September 30, 2024. The award is provided through the NSF's Computer and Information Science and Engineering program (CFDA 47.070), which...
The University of Virginia received a three-year, $388,000 Project Grant award from the National Science Foundation Division of Electrical, Communications and Cyber Systems to support the research project "Blind Carbon Copy on Dirty Paper: Seamless Spectrum Underlay Made Practical" from July 1, 2021 through June 30, 2024. The grant is funded through the NSF Engineering Program (CFDA 47.041), which aims to improve quality of life and economic strength through innovative engineering...
The University of Virginia (UVA) received a $600,000 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) to advance federated graph machine learning (FGML) techniques. The project aims to 1) address data heterogeneity challenges in FGML, 2) develop novel algorithms to tackle label deficiency issues, and 3) strengthen data privacy protection for node attributes and graph structures. The research will produce...
This Project Grant from the National Science Foundation's $299,152 Computer and Information Science and Engineering program will fund research exploring a new approach to digital communication based on state synchronization. Led by Washington University, the award will formalize the semantics and analytical framework for a synchronization model of communication as an alternative to traditional transmit-receive and request-response internet protocols. Over the one-year period from October 1, 2022...
The National Science Foundation awarded a $1,498,658 project grant under the Engineering (47.041) federal grant program to the University of Virginia. The grant, entitled "ASCENT: FERROELECTRIC-BASED COMPUTE-IN-MEMORY DYNAMICAL ENGINE (FERRO-CODE) TO SOLVE HARD COMBINATORIAL OPTIMIZATION," aims to develop a ferroelectric-based compute-in-memory dynamical engine to solve hard combinatorial optimization problems. The University of Virginia will lead the effort to design hardware and...
The University of Virginia (UVA) received a $197,290 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to conduct collaborative research on security and privacy in machine unlearning. The project aims to better understand and defend against security and privacy risks that may arise from the use of machine unlearning techniques, which allow companies to remove the influence of personal data from their...