Project Grant 2310504
- The National Science Foundation (NSF) awarded a $249,989 project grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of New Hampshire's (UNH) Office of Sponsored Research. The grant supports the development of efficient and robust statistical tools for modeling data with measurement errors, a common challenge in fields like epidemiology and economics. The research aims to improve estimation accuracy and hypothesis testing power across linear, nonlinear, and...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $225,000 Project Grant to Carnegie Mellon University to develop a methodology for simulation-based inference that uses random features rather than carefully designed summary statistics. The 3-year grant, which runs from August 15, 2023 to July 31, 2026, aims to create a practical and generic tool for fitting simulation models to real-world data across diverse domains like astronomy, ecology, climate science, and...
- 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...
- This $152,997 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research at the University of Southern California (USC) on computer-intensive statistical inference methods for high-dimensional and massive datasets. The project aims to develop efficient, scalable, and statistically robust inferential procedures for two classical problems - change point detection/identification and computationally-aware statistical...
- This $150,000 Project Grant from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) will fund the development of new clustering techniques and software packages at San Jose State University. The awardee will create a family of versatile mixture models to analyze mixed-type data with asymmetry, outliers, and missing values. Novel statistical approaches and latent class models will allow the techniques to handle high-dimensional, continuous, discrete,...
- This $299,965 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences will allow Colorado State University (CSU) to develop and validate a new statistical model and analytical methods for assessing extremal dependence in high-dimensional data. This work aims to improve quantification of joint risks in applications such as finance, insurance, and climate science. The project will include training a graduate student in extreme value analysis techniques...
- This National Science Foundation (NSF) Division of Mathematical Sciences Project Grant, awarded to Carnegie Mellon University, provides $240,000 in funding from September 1, 2023 to August 31, 2026. The grant supports research to advance statistical predictive inference methods, addressing challenges in areas like cross-validation, high-dimensional statistical comparisons, and conformal prediction. The project aims to develop novel techniques with strong mathematical justifications that can...
- The University of California, San Diego (UCSD) received a $300,000 Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) program. The grant supports the development of advanced computational and statistical methods for analyzing complex, dependent data from diverse scientific domains such as climate, economics, and neuroimaging. Key research thrusts include subsampling and resampling techniques for large datasets, robust...
- 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...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $100,000 Project Grant to the University of Central Florida (UCF) to develop efficient and effective algorithms for detecting anomalies in high-dimensional spatiotemporal data with large amounts of missing data. Under CFDA 47.049 - Mathematical and Physical Sciences, the project aims to address the challenge of predicting rare anomalies using high-dimensional real-world data with mixed-type multivariate response,...
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 regression and classification techniques for nonstandard data structures to improve predictive modeling accuracy. This includes deriving performance bounds for proposed estimators in various norms. Designing efficient virtual resampling strategies to accelerate computational-intensive bootstrap methods for large datasets, particularly for multiple hypothesis testing and errors-in-variables models. The grant period runs from September 1, 2023 to August 31, 2026 and will provide research experiences for graduate and undergraduate students to encourage STEM career paths.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $200.0k | 6/29/23 |