Project Grant 2210216
- This $400,000 National Science Foundation Project Grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of statistical methods and machine learning techniques for analyzing complex structured and count data. Over a three-year period ending in August 2025, the University of Washington will advance the state of knowledge in big structured and count data analysis through two tracks of research. The first track will focus on revising and...
- Federal Grant Award Summary The University of Washington received a $125,000 Project Grant from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049), awarded on September 15, 2025, with a completion date of August 31, 2028. This collaborative research project develops theoretical foundations and methodological advances for causal learning from complex machine learning algorithms. The primary products include...
- Federal Project Grant Award Summary The National Science Foundation's Division of Mathematical Sciences awarded $250,000 to the University of Washington (awarded September 15, 2025; completion date August 31, 2028) under the Mathematical and Physical Sciences program (CFDA 47.049) to conduct research on prediction-powered inference (PPI) and semi-supervised learning. The project delivers three integrated research products: (1) theoretical advances establishing semi-parametric efficiency...
- This $300,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of next-generation mathematical and algorithmic tools to address two key issues in applying machine learning to statistical modeling of time-evolving complex systems: a shortage of informative training data and the high computational costs of high-dimensional problems. Specifically, the...
- Federal Grant Award Summary The University of Washington received a $325,000 Project Grant from the National Science Foundation (NSF) Division of Social, Behavioral and Economic Science under the Social, Behavioral, and Economic Sciences program (CFDA 47.075), effective September 15, 2025 through August 31, 2028. This award supports the development of graph-based statistical and machine learning methods for analyzing complex, high-dimensional data including manifold data with hidden geometric...
- This three-year, $260,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will fund research towards designing optimal statistical learning procedures through precise medium-dimensional asymptotic analysis. The grantee, Columbia University, will develop a novel analytical framework to quantitatively characterize the performance of diverse learning algorithms and provide guidance on...
- Federal Project Grant Award Summary The University of Washington received a $249,652 Project Grant from the National Science Foundation's Division of Mathematical Sciences (CFDA 47.049—Mathematical and Physical Sciences) effective September 15, 2026, with a completion date of August 31, 2029. The award funds the development of novel statistical machine learning tools and theoretical frameworks for analyzing neuronal spike train data in the spectral domain to infer brain functional connectivity...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $200,000 Project Grant to The University Corporation, a non-profit organization located in Northridge, CA. The grant, funded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), focuses on developing new statistical modeling and data resampling methods to address challenges posed by incomplete, missing, and fragmented observations in large datasets. Key objectives include: Advancing...
- Federal Project Grant Award Summary The National Science Foundation (NSF) Division of Mathematical Sciences awarded $250,000 to the University of Wisconsin - Madison under the Mathematical and Physical Sciences program (CFDA 47.049) on July 1, 2026, for a three-year project extending through June 30, 2029. The project develops statistical foundations and methodology for the reliable integration of artificial intelligence (AI)-generated synthetic datasets into scientific estimation, prediction,...
- 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 a $350,000 Project Grant to the University of Washington under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) to develop novel strategies for constructing optimal statistical estimators using machine learning tools. Over a three-year period ending August 2025, the investigators will study representations of the efficient influence function that can be computed numerically to derive new asymptotically efficient estimators. They will also use reinforcement learning techniques to adversarially learn minimax optimal statistical procedures for broad applicability. In addition to advancing statistical methodology, the project aims to engage undergraduates in research and mentor graduate students, with potential applications to vaccine clinical trial data analysis.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $175.0k | 6/16/22 |