Project Grant 2515788
- This $125,627 federal Project Grant award, funded by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049), will support collaborative research to develop advanced statistical tools for analyzing large-scale biomedical imaging data. The research aims to overcome key challenges in causal analysis of imaging outcomes, including addressing issues such as unmeasured confounding and population heterogeneity. The project, led by Iowa State University, will...
- The National Science Foundation awarded $150,000 to Regents of the University of California at Riverside under the Mathematical and Physical Sciences program (CFDA 47.049) from July 1, 2023 to June 30, 2026. The Project Grant funding will support research to develop new statistical methodologies and deep learning techniques for uniformly estimating causal effects of continuous treatments using large observational health data sets. Specifically, the university will design neural network...
- This $162,490 federal Project Grant awarded by the National Science Foundation's (NSF) Division of Mathematical Sciences will fund collaborative research at Virginia Polytechnic Institute & State University (Virginia Tech) to develop advanced, memory-efficient algorithms and solvers for high-dimensional imaging applications such as medical imaging and video compression. The project aims to achieve significant improvements over existing state-of-the-art methods by leveraging data properties...
- This National Science Foundation Project Grant of $220,000 supports research into statistical modeling methods for large, complex datasets. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the University of California, San Francisco will develop new Bayesian regression techniques using random data compression matrices. These approaches aim to enable efficient, scalable inference and prediction from high-dimensional biomedical data sources like brain imaging, genetics,...
- This $229,461 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports the development and analysis of novel self-supervised probabilistic graph structure learning models. The goal is to uncover latent representations hidden within large datasets, which can provide valuable insights across diverse applications like cancer research and environmental analysis. The research will involve creating advanced mathematical models,...
- 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 $162,510 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences will fund collaborative research at Tufts University to develop innovative, memory-efficient algorithms for high-dimensional imaging applications such as medical imaging, object inspection, and video surveillance. The key products will be accelerated reconstruction and compression techniques that can process large volumes of multi-dimensional imaging data in real-time while using...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $125,667 Project Grant to Virginia Polytechnic Institute & State University (Virginia Tech) under the Mathematical and Physical Sciences program (CFDA 47.049). The grant will fund collaborative research to develop new theories and methodologies for multiple hypothesis testing on regression analysis, which is critical for analyzing high-dimensional data in the era of big data. The research project will create...
- This $289,999 National Science Foundation project grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), will fund the development of improved statistical methods, algorithms, and theory for estimation and inference with high-dimensional data at Rutgers, The State University from July 2022 through June 2025. Key products include new statistical methods for regularized estimation, de-biased statistical inference including confidence intervals and regions, and empirical...
- This $155,372 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will fund research to develop advanced statistical methods for extracting insights from high-dimensional, high-frequency "big data." The University of Illinois, Chicago, as the prime awardee, will focus on four key areas: 1) advancing contiguity theory to enable more robust statistical analysis of noisy, high-frequency data; 2) exploring time-varying...
This $124,487 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences Program (CFDA 47.049) will fund research to develop advanced statistical tools and techniques for analyzing large-scale biomedical imaging data. The research aims to overcome key challenges in causal analysis of imaging outcomes, including handling computational demands and addressing issues like unmeasured confounding and population heterogeneity. The resulting data analytics tools are expected to have broad applicability across various fields, including aging research, digital health, and plant science. The award will support the research efforts of the Rector & Visitors of the University of Virginia, a prominent public research university, over a 3-year period from September 1, 2025 to August 31, 2028. The project will also benefit the broader research community through the release of freely available software tools and support STEM education by involving students in the research.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $124.5k | 7/23/25 |