Project Grant 2515246
- This federal Project Grant award of $100,000.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research by Purdue University to develop advanced statistical methods for improving signal recovery and noise reduction in multiscale data domains. The key products and services to be delivered include: Innovative shrinkage and thresholding techniques applied in multiscale domains like wavelets to simplify complex data by...
- 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 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 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 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...
- This $175,000 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will fund research to develop new statistical and computational methods to enhance the reliability of data analysis in modern, large-scale datasets, particularly in the era of AI. The key areas of focus include: (1) analyzing the robustness of manifold and deep learning algorithms for high-dimensional, noisy, and nonlinear data; (2) developing statistical theory...
- 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...
- This federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) focuses on developing new frequency domain modeling techniques for analyzing high-dimensional time series data. The $177,718 award to Southern Methodist University (SMU) will fund research to create a new modeling framework that enables dimension reduction and correlation analysis of large, complex time series datasets across disciplines such as neuroscience,...
- This National Science Foundation Project Grant award of $359,976 provides funding from June 15, 2022 through May 31, 2025 to develop new statistical methods for scalable inference in high-dimensional structured regressions. The awardee is Texas A&M University under the Mathematical and Physical Sciences program (CFDA 47.049). Specifically, the researchers will develop approaches based on compressing large datasets using random linear transformations prior to fitting statistical models....
- This $227,796 Project Grant awarded by the National Science Foundation's (CFDA 47.049 - Mathematical and Physical Sciences) focuses on developing new mathematical techniques to more effectively analyze signals by carefully isolating their distinct parts in time, space, or frequency. The research aims to improve understanding of spatio-spectral limiting operators, which can significantly enhance everyday technologies like MRI machines, wireless communications, and scientific imaging. In...
This Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) supports the development of novel Bayesian thresholding and shrinkage methods for extracting meaningful information from large, noisy datasets across diverse scientific and engineering domains. The $100,123 award to Texas A&M University, which runs from Sep 1, 2025 to Aug 31, 2028, focuses on advancing statistical techniques for signal recovery and noise reduction in multiscale settings, including the exploration of quantum-inspired shrinkage approaches. The research aims to simplify complex data while preserving essential features, leading to more accurate and interpretable results. The project also integrates educational components through student mentoring, course integration, and the creation of open-source software tools to promote reproducible research and broader access to cutting-edge statistical methodologies.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $100.1k | 8/14/25 |