The University of Utah was awarded a $499,384 project grant from the National Science Foundation to support research titled "AF: SMALL: THE GEOMETRY OF LEARNING ON STRUCTURED DATA OBJECTS" from October 1, 2021 to 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, and information science and engineering....
The University of Utah will receive $614,956 from the National Science Foundation under the Computer and Information Science and Engineering program (CFDA 47.070) to develop acceleration strategies for emerging life science workloads through an AI+X approach from October 1, 2022 to September 30, 2025. Specifically, the project will design configurable accelerator architectures to efficiently handle both artificial intelligence and small-market healthcare domains like computational pathology...
The University of Utah will receive $411,248 over three years from the National Science Foundation under the Computer and Information Science and Engineering program (CFDA 47.070) to support the project "SMALL: SELF-ADAPTIVE OPTIMIZATION ALGORITHMS WITH FAST CONVERGENCE VIA GEOMETRY-ADAPTED HYPER-PARAMETER SCHEDULING." This Project Grant will fund research to develop self-adaptive optimization algorithms that can rapidly converge via geometry-adapted hyper-parameter scheduling. The...
The University of Utah received a $220,500 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). This 5-year award, beginning March 1, 2024, supports research to develop scalable security testing techniques for large software systems. The project focuses on advancing "fuzzing" - a predominant software vulnerability detection method - to address the unique challenges posed by software...
The University of Utah received a $104,794 Project Grant award from the National Science Foundation Division of Mathematical Sciences on January 15, 2021 to support collaborative research titled "ROBUST, ACCURATE AND EFFICIENT GRAPH-STRUCTURED RNN FOR SPATIO-TEMPORAL FORECASTING AND ANOMALY DETECTION." The period of performance for this award is January 15, 2021 through December 31, 2022. The award supports research under the Mathematical and Physical Sciences program (CFDA 47.049)...
The University of Utah was awarded a $409,494 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports collaborative research titled "MICROSTRUCTURE BY DESIGN: INTEGRATING GRAIN GROWTH EXPERIMENTS, DATA ANALYTICS, SIMULATION, AND THEORY" from September 1, 2021 to August 31, 2025. The research aims to advance understanding of major problems in materials science through...
The University of Utah will receive $500,000 over three years from the National Science Foundation Division of Research on Learning in Formal and Informal Settings under the Computer and Information Science and Engineering program (CFDA 47.070) to conduct research titled "COLLABORATIVE RESEARCH: NCS: FO: ENHANCING EPISODIC MEMORY THROUGH REAL-WORLD INTEGRATION OF BRAIN RECORDING AND STIMULATION WITH SEMANTIC ALIGNMENT OF HUMAN AND IOT PERCEPTION." The research aims to advance...
This $126,025 five-year Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) aims to advance machine learning techniques through the development of new mathematical tools for analyzing and visualizing complex, high-dimensional data. The key objectives are to create robust manifold learning algorithms that can handle noisy data, preserve local and global geometric details, and effectively cluster collections of manifolds. The...
This $439,425 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research to enable the safe deployment of learning-enabled systems that can robustly learn and optimize their behavior based on uncertain human feedback and intent. The key objectives are to: (1) develop methods for providing probabilistic performance guarantees when learning policies from human input,...
This $819,000 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) will fund a collaborative research project titled "SCIOPT: Toward Certifiable Compression-Aware SCIML Systems" at the University of Utah. The project aims to develop techniques to reduce the volume of data exchanged in high-performance scientific simulations and scientific machine learning (SCIML) applications without sacrificing accuracy. Key...