Project Grant 2312173
- The National Science Foundation awarded a $225,000 Project Grant to Texas A&M University under the Mathematical and Physical Sciences program (CFDA 47.049) for the period of November 1, 2021 through October 31, 2024. The grant funds collaborative research on new perspectives for deep learning by bridging approximation, statistical, and algorithmic theories. The Mathematical and Physical Sciences program aims to advance scientific knowledge and understanding in core areas of mathematics and...
- Federal Grant Award Summary Texas A&M University received a $239,850 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), effective August 15, 2025, with a completion date of July 31, 2028. The project develops and advances optimal recovery theory—a mathematical framework that provides worst-case performance guarantees for function learning and recovery algorithms under realistic...
- Federal Project Grant Award Summary Texas A&M University received a $100,123 Project Grant award from the National Science Foundation's Division of Mathematical Sciences (CFDA 47.049: Mathematical and Physical Sciences) effective September 1, 2025, through August 31, 2028. The award supports collaborative research developing advanced Bayesian thresholding and shrinkage methods for signal recovery and noise reduction in multiscale domains, with primary applications in medical imaging,...
- This National Science Foundation (NSF) Project Grant award, under the Mathematical and Physical Sciences (CFDA 47.049) program, will support research on stochastic methods and isoperimetric inequalities at Texas A&M University. The $238,406 award, active from July 2024 to June 2027, will develop techniques to bridge fundamental conjectures in Brunn-Minkowski theory and dual Brunn-Minkowski theory, with a focus on intersection bodies and higher-dimensional generalizations. The research aims...
- The National Science Foundation awarded Texas A&M University a $350,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) from September 1, 2023 to August 31, 2026. The university will develop Bayes factor functions to provide standardized measures of the evidence from scientific studies. Researchers will define the functions directly from classical test statistics and model distributions based on effect sizes. This will allow scientists across various...
- The National Science Foundation awarded a $169,977 Project Grant to Texas A&M University under the Mathematical and Physical Sciences program (CFDA 47.049) to support research titled "ROBUST AND EFFICIENT STATISTICAL INFERENCE IN LARGE SCALE SEMI-SUPERVISED SETTINGS." The three-year award, which runs from August 1, 2021 through July 31, 2024, will fund the development of statistical methods to enable robust and efficient inference on large, semi-supervised datasets. As the prime...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
- Federal Grant Award Summary Texas A&M University received a $199,581 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded August 15, 2025, with completion targeted for July 31, 2027. The project focuses on advancing mathematical research in metric invariants and geometric analysis through investigation of the Kalton Program and Ribe Program frameworks. The principal...
- This Project Grant award from the National Science Foundation's Mathematical and Physical Sciences (CFDA 47.049) program provides $140,889 to Texas A&M University to conduct research connecting machine learning and numerical methods for partial differential equations. The key objectives are to leverage deep learning techniques to improve numerical methods for PDEs, and apply the theoretical understanding of finite element methods to better comprehend the success of deep neural networks....
- The National Science Foundation Division of Mathematical Sciences awarded a $149,783 Project Grant to Texas A & M University from July 2021 through June 2024 under the Mathematical and Physical Sciences program (CFDA 47.049). The grant funds research titled "CDS & E-MSS: OPTIMAL RECOVERY IN THE AGE OF DATA SCIENCE" to promote progress in the mathematical and physical sciences. Specifically, the university will leverage data science techniques to advance understanding of major...
The National Science Foundation Division of Mathematical Sciences awarded Texas A&M Engineering Experiment Station a $180,000 Project Grant under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) from August 1, 2023 through July 31, 2026. The award will support research to develop a systematic approach for constructing deep Bayesian neural networks that are both computationally efficient and amenable to model designs. The research is expected to lead to improvements in accuracy, confidence, and efficiency over current machine learning models. Open-source software will also be developed to provide accessible tools for researchers and practitioners. The research is aimed at advancing deep Gaussian process models and relevant Bayesian neural networks in areas including theory, algorithms, generative applications, and software validation using real-world datasets.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $180.0k | 6/15/23 |