Project Grant 2513928
- Federal Project Grant Award Summary Southern Methodist University received a $2.15 million Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering program (CFDA 47.070), awarded April 1, 2026, with a completion date of March 31, 2031. The project, titled "Framework for Advanced (Multi)Linear Infrastructure in Engineering and Science (FAMLIES)," delivers an adaptable, open-source software...
- Federal Grant Award Summary Carnegie Mellon University received a $1.395 million Project Grant from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070). The award, effective April 1, 2026, through March 31, 2031, supports the development of the Framework for Advanced (Multi)linear Infrastructure in Engineering and Science (FAMLIES). This collaborative research initiative delivers an...
- 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...
- Federal Project Grant Award Summary The University of Texas at Austin received a $225,000 Project Grant from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049), effective September 1, 2025, through August 31, 2028. This collaborative research initiative develops a unified neurosymbolic reasoning and formal verification system that integrates artificial intelligence with rigorous mathematical proof techniques. The project addresses the...
- Federal Grant Award Summary The University of Texas at Austin received a $333,000 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems (CISE Program, CFDA 47.070) awarded October 1, 2025, with completion targeted for September 30, 2028. This collaborative research initiative develops a novel neurosymbolic programming framework called Foundation Model Programming designed to generate symbolically interpretable scientific hypotheses from...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $322,730 Project Grant to the University of Texas at Austin from September 1, 2023 to August 31, 2026. The grant is funded under NSF's Mathematical and Physical Sciences Program (CFDA 47.049) and aims to develop techniques for assessing the accuracy of randomized algorithms used to solve fundamental linear algebraic equations in computational science. The project will focus on improving the speed and robustness...
- Award Summary The University of Texas at Austin received a $399,998 Project Grant from the National Science Foundation's Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) for the period August 1, 2025 through July 31, 2028. The award supports research on "Numerical Scheme-Guided Deep Learning for Scientific Computing," which develops innovative algorithms that integrate classical numerical schemes with deep learning paradigms to...
- Federal Grant Award Summary The National Science Foundation's Division of Materials Research awarded a $1.5 million Project Grant to the University of Texas at Austin on October 1, 2025, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop MATCSSI 2.0, a cloud-integrated platform that democratizes access to advanced many-body electronic structure computational methods. The project, which extends through September 30, 2028, addresses the mathematical complexity and...
- This $256,710 National Science Foundation award under the Computer and Information Science and Engineering (CFDA 47.070) program supports a collaborative research project led by the University of Texas at Austin. The project investigates full-stack implementation methodologies for developing expressive programming systems that bridge the gap between high-level specifications and high-performance implementations of complex reasoning tasks at scale. Key focus areas include extending declarative...
- The University of Texas at Austin received a $1,278,970 project grant award from the National Science Foundation Office of Advanced Cyberinfrastructure to support research titled "COLLABORATIVE RESEARCH: FRAMEWORKS: CONVERGENCE OF BAYESIAN INVERSE METHODS AND SCIENTIFIC MACHINE LEARNING IN EARTH SYSTEM MODELS THROUGH UNIVERSAL DIFFERENTIABLE PROGRAMMING" from August 1, 2021 through July 31, 2025. The grant is part of the NSF's Computer and Information Science and Engineering program...
The University of Texas at Austin received a $703,154 Project Grant award from the National Science Foundation's Office of Advanced Cyberinfrastructure under the Computer and Information Science and Engineering (CFDA 47.070) program, effective April 1, 2026 through March 31, 2031. This collaborative research initiative delivers the Framework for Advanced (Multi)Linear Infrastructure in Engineering and Science (FAMLIES), an adaptable software framework designed to optimize matrix and tensor computations across the full high-performance computing hardware stack. The framework vertically integrates software layers to support critical applications in drug design, quantum computing development, and artificial intelligence architecture development while reducing computational resource demands and hardware costs. FAMLIES is released under open-source license and modernizes dense linear algebra software libraries that have been foundational to scientific computing over the past four decades. The framework enhances flexibility and convenience for cutting-edge applications requiring new functionality and rapid development cycles, while simultaneously reducing barriers to entry for computational and data scientists. By building upon highly successful prior research in linear algebra computing, the project supports innovation across science and engineering disciplines and facilitates the training of the next generation of computational scientists through accessible, adaptable software infrastructure.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $703.2k | 3/26/26 |