Project Grant 2515303
- This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) provides USD 125,000 in funding to the University of California, Davis to advance the field of Generalized Fiducial Inference (GFI). The key objectives are to extend GFI methods to causal inference models, particularly instrumental variable models, and redefine GFI through normalizing flows to manage computational complexity in non-analytic scenarios. The project...
- This three-year Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences federal grant program (CFDA 47.049), provides $320,000 to the University of North Carolina at Chapel Hill to conduct collaborative research on emerging variants of generalized fiducial inference. The research aims to explore the evolution of the fiducial argument as a response to modern data science questions and techniques. Researchers will develop...
- This National Science Foundation Project Grant award of $340,000 provides funding from September 1, 2022 through August 31, 2025 to support collaborative research on emerging variants of generalized fiducial inference. The award is made under the Mathematical and Physical Sciences program (CFDA 47.049) to further the Foundation's mission of advancing the mathematical and physical sciences. Specifically, the University of California, Davis will conduct research to develop easy-to-implement...
- The National Science Foundation (NSF) awarded a $299,978 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to the University of North Carolina at Chapel Hill (UNC-CH). This 3-year grant, effective from August 1, 2025 to July 31, 2028, will fund research to develop mathematical foundations and statistical methods for analyzing complex geometric data. The project focuses on data types that arise in diverse scientific and societal contexts, such as...
- This $275,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support collaborative research to develop new statistical approaches for comparing and aligning networks. The research will focus on investigating optimal transport-based distances for Markov embeddings of networks, developing new methods for network alignment and comparison, and establishing theoretical results about these approaches. The...
- This Project Grant award of $160,000 from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research at North Carolina State University (NC State) on "Partial Priors, Regularization, and Valid & Efficient Probabilistic Structure Learning." The research aims to develop new statistical methods for reliable uncertainty quantification in high-dimensional structure learning problems that are ubiquitous across the...
- This $155,000 project grant awarded by the National Science Foundation (NSF) under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) will develop new simulation-based inference (SBI) methods. These innovations aim to empower scientists to make better use of complex models across diverse domains such as genetics, ecology, biology, economics, and psychology, supporting more scalable, efficient, and reliable decision-making. The project will address two core challenges...
- This $149,989 Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support research to develop statistical models and inference methods for analyzing random point processes. The research will provide tools for analyzing time series of point process data, with applications in fields such as national security, economics, neuroscience, and geosciences. Key activities include developing parameter estimation procedures,...
- This $169,999 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports collaborative research at the University of California, Davis (UC Davis) to advance innovative nonparametric data analysis techniques. The project aims to conduct comprehensive statistical and computational analyses to push the boundaries of modern nonparametric statistical inference, with potential applications in areas like nonparametric latent...
- The National Science Foundation (NSF) awarded a $108,000 Project Grant under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) to the University of Illinois for the collaborative research project "Distributional Balancing Methods for Advancing Causal Inference in Complex Settings". The project aims to develop advanced statistical methodologies that improve the reliability of causal conclusions from complex, observational data. Specifically, it will enhance...
This Project Grant award, provided by the National Science Foundation under the Mathematical and Physical Sciences (CFDA 47.049) program, supports collaborative research to advance Generalized Fiducial Inference (GFI) methods. The $125,000 award to the University of North Carolina at Chapel Hill aims to extend GFI techniques for causal inference models and redefine GFI through normalizing flows to address computational complexities in non-analytic scenarios. The research will apply these innovations to real-world problems in forensic science, social network learning, and sports analytics, enhancing decision-making processes across diverse fields. The project also provides valuable research training opportunities for STEM graduate students, contributing to national goals of promoting scientific advancement, health, prosperity, and welfare. No sub-awards are planned under this grant.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $125.0k | 8/14/25 |