Project Grant 2210064
- 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 $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...
- This National Science Foundation (NSF) Project Grant under the Mathematical and Physical Sciences (CFDA# 47.049) program will fund a collaborative research effort between U.S. and U.K. investigators to develop new statistical methods for modeling dynamic changes in biological and other complex shapes. The $200,000 award, effective August 1, 2024 through July 31, 2027, will focus on integrating spatiotemporal registration of objects and their evolution into the statistical formulation to enable...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) is funding collaborative statistical research and methodology development for analyzing object-valued time series data. The $174,344 award to The Washington University, which began on January 1, 2025, will support the development of new models, techniques, and theory for statistical inference and change detection in object-valued time series across various scientific and...
- 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 $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 Project Grant award from the National Science Foundation (CFDA 47.049 - Mathematical and Physical Sciences) in the amount of $197,007 is supporting collaborative research to develop new statistical theories and methodologies for tackling issues related to false discovery rate control in regression analysis. The research aims to provide novel statistical tools for analyzing complex data from diverse scientific domains such as brain imaging, genome-wide association studies, and atmospheric...
- This $121,153 Project Grant awarded by the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program will support research to develop advanced statistical methods for analyzing complex spatial point process data. The key products and services to be delivered include: Developing nonparametric Bayesian models to reveal hidden spatial homogeneity and heterogeneity within and across univariate and multivariate spatial...
- This $365,274 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of novel mathematical techniques and algorithms for designing cost-effective space-time sampling strategies and reconstruction methods for time-evolving functions on graphs. A diverse group of researchers from Northern Illinois University will work to analyze and manage various time-evolving processes sampled under realistic conditions and...
- 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 National Science Foundation project grant of $239,962 will support the development of novel statistical methods for analyzing functional and imaging data supported on complex geometries through the Mathematical and Physical Sciences program (CFDA 47.049). Led by the University of Washington with a completion date of June 2025, key products include generalized linear models and regularized linear models to predict outcomes from functional predictors on multidimensional non-linear domains. Methods will leverage tools from partial differential equations, calculus of variations, and numerical analysis to efficiently approximate solutions. The framework will also be extended to tensor-structured functional predictors controlled via low-rank constraints. Software implementations of the new models will be publicly released, offering opportunities for interdisciplinary training. Overall, this award aims to advance the analysis of modern imaging data on complex surfaces like the brain cortex through statistical and computational methodology.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $120.0k | 6/6/22 |