The University of Texas at Austin received a $451,486.58 Project Grant award from the Department of Energy's Office of Science Financial Assistance Program (CFDA 81.049) to conduct accelerated research in quantum computing. The award period runs from September 1, 2024 to August 31, 2025. This grant supports the university's cutting-edge interdisciplinary research initiatives focused on advancing quantum computing capabilities. The project leverages UT Austin's expertise in areas such as...
The U.S. Department of Energy's Office of Science awarded a $550,302 Project Grant to the University of Rochester for the project "TENSOR NETWORK DECOMPOSITION OF OPEN QUANTUM DYNAMICS FOR EFFICIENT SIMULATION OF NEXT-GENERATION QUANTUM SYSTEMS". This award under the Office of Science Financial Assistance Program (CFDA 81.049) supports fundamental scientific research to advance U.S. energy, economic, and national security priorities. The project aims to develop novel tensor network...
The U.S. Department of Energy's Office of Science awarded a $899,990 Project Grant to Trustees of Tufts College (Tufts University) under the Office of Science Financial Assistance Program (CFDA 81.049). The grant, effective September 1, 2024 through August 31, 2025, supports the research project "TENSOR-BASED STREAMING ALGORITHMS FOR SCIENTIFIC DATA COMPRESSION." Tufts University, a private research institution in Medford, Massachusetts, will leverage its expertise in computer science,...
This five-year, $7.3 million project grant from the National Science Foundation's Computer and Information Science and Engineering program aims to develop a comprehensive framework for efficient, scalable, and performance-portable tensor applications. The University of Utah will receive funding to collaborate with other researchers on advancing tensor computations, which are fundamental to large-scale parallel software applications in scientific computing and machine learning. Key deliverables...
This Project Grant award of $1,530,000.00 from the U.S. Department of Energy's Office of Science Financial Assistance Program (CFDA 81.049) supports a pathway program for talent preparation focused on modeling and manufacturing of novel materials and structures for fusion energy. The award was granted to the University of Texas Rio Grande Valley (UTRGV) and will run from January 1, 2025 to December 31, 2025. The program aims to advance research, technological innovation, and the development of...
The National Science Foundation Office of Advanced Cyberinfrastructure awarded the University of Texas at Austin a $1.2 million Project Grant under the Computer and Information Science and Engineering program (CFDA 47.070) from September 1, 2022 to August 31, 2025. The grant funds research to develop a rigorous and reliable scientific deep learning framework for forward, inverse, and uncertainty quantification problems in computational science and engineering. Specific objectives include...
This $540,000 Project Grant award, provided by the Department of Energy's Office of Science Financial Assistance Program (CFDA 81.049), supports a research project titled "TENSOR-BASED STREAMING ALGORITHMS FOR SCIENTIFIC DATA COMPRESSION" to be conducted by North Carolina State University (NC State). This research aims to develop innovative tensor-based streaming algorithms to enable efficient compression of large scientific datasets. NC State, a prominent 1862 Land Grant...
This National Science Foundation Project Grant of $229,021 awarded on August 1, 2022 will support research at the University of Texas at Austin to develop mathematical frameworks in optimal transport applications to probability, machine learning, and kinetic theory through July 31, 2025. Under the Mathematical and Physical Sciences program (CFDA 47.049), the investigator will advance understanding of stochastic modeling, artificial intelligence algorithms, and kinetic theory by exploiting...
Texas Tech University was awarded a $237,111 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The grant will support research titled "Adaptive High Order Low-Rank Tensor Methods for High-Dimensional Partial Differential Equations with Application to Kinetic Simulations" being conducted from August 2021 through July 2024. The research aims to develop new computational...
This $260,000 National Science Foundation project grant will fund the development of data-enabled modeling, monitoring, and optimization algorithms targeting power system dynamics from 2022-2025. The University of Texas at Austin, through its parent organization the University of Texas System, will receive funding under the NSF Engineering program (CFDA 47.041) to correlate synchrophasor data and develop Gaussian process and stability-aware optimal power flow tools. Key outcomes will include...