Project Grant 2109155
- 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...
- The National Science Foundation awarded a $441,331 project grant to the University of Texas at Austin under the Mathematical and Physical Sciences program (CFDA 47.049). The grant supports research across three topics in stochastic analysis from June 2023 through May 2026. The university will examine Kyle models to study information exchange in financial markets, use backward stochastic differential equations to analyze strategic behavior, and investigate dynamics of fluctuations in financial...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $399,998 to the University of Texas at Austin (UT Austin) to develop innovative numerical algorithms that integrate classical numerical schemes and deep learning techniques. The goal is to address complex scientific computing challenges, such as simulating high-dimensional, fully nonlinear differential equations, long-term Hamiltonian system simulations, and...
- This Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), provides $429,148 to the University of Texas at Austin for collaborative research on randomized feature methods for modeling and dynamics from September 1, 2022 to August 31, 2025. The research aims to develop consistent and theoretically validated machine learning algorithms for high-stakes decisions by studying randomized feature...
- The University of Texas at Austin was awarded a $409,550 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The three-year award running from July 1, 2021 to June 30, 2024 will support research developing models and algorithms for optimal vision-based surveillance and exploration of complex environments. The funding will enable work advancing scientific understanding of major...
- This $175,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports the development of novel Bayesian statistical frameworks to address measurement error challenges in complex multivariate data. The project aims to create more flexible, data-driven methods that can reliably identify meaningful patterns and relationships from noisy, imprecise observations - a common issue in fields like health research, astronomy, and...
- The University of Texas at Austin was awarded a $220,000 Project Grant from the National Science Foundation Division of Electrical, Communications and Cyber Systems. The award is part of the Engineering (47.041) federal grant program to support collaborative research titled "CCSS: LEARNING TO OPTIMIZE: FROM NEW ALGORITHMS TO NEW THEORY" from August 15, 2021 to July 31, 2024. Under this award, the University of Texas at Austin will conduct research to develop new algorithms and...
- The University of Texas at Austin was awarded a $270,000 project grant from the National Science Foundation Division of Mathematical Sciences to support research titled "DIRECT FINITE ELEMENTS ON CONVEX POLYGONS AND POLYHEDRA" from September 1, 2021 to August 31, 2024. Under the grant, the University will conduct research into direct finite element methods on convex polygons and polyhedra. The research is part of the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which...
- 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...
- The University of Texas at Austin received a $561,000 Project Grant award from the National Science Foundation on November 15, 2021 to complete the project by September 30, 2024. The grant was awarded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), which supports progress in these scientific fields to strengthen the nation's scientific enterprise. Specifically, the university will conduct research to modulate metalloprotein activities through fine-tuning reduction...
The University of Texas at Austin was awarded a $299,966 Project Grant from the National Science Foundation Division of Mathematical Sciences on September 1, 2021, with a completion date of August 31, 2024. The award is being used to support the "LEARNING WITH CONFIDENCE: BOOTSTRAPPING ERROR ESTIMATES FOR STOCHASTIC ITERATIVE ALGORITHMS" project under the Mathematical and Physical Sciences program (CFDA #47.049). The project aims to develop new techniques for estimating errors in stochastic iterative algorithms, which introduce randomness into computations to solve complex problems. By providing more reliable error bounds, the research is intended to boost confidence in solutions generated by such probabilistic methods. The results could help advance mathematical and physical sciences applications that rely on stochastic simulations to study challenging systems. The three-year period will allow for in-depth investigation and testing of novel error estimation approaches for this class of numerical algorithms.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $300.0k | 7/9/21 |