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...
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...
The National Science Foundation (NSF) awarded a $174,344 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to The Washington University in University City, Missouri. The grant supports collaborative research to develop new statistical models, methodology, and theory for the analysis of object-valued time series data. Key objectives include: (1) creating a new autoregressive model and associated tools for distributional time series analysis in Wasserstein...
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 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...
This Project Grant award, funded by the National Science Foundation (NSF) through the Mathematical and Physical Sciences (CFDA 47.049) program, is supporting research on statistical inference for multivariate and functional time series data. The $146,738 award to The Washington University will develop a new unified framework based on sample splitting and self-normalization to enable robust inference for time series data of varying dimensionality. The research aims to address limitations of...
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...
This $375,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research at the Massachusetts Institute of Technology (MIT) to advance the understanding of statistical analysis within a broader environment with multiple stakeholders. The project aims to develop statistical protocols that are robust to the behavior of different stakeholders who may have different aims, in order to enable more reliable...
The National Science Foundation awarded a $252,937 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to the University of Chicago. The purpose of this 3-year grant, which runs from September 1, 2023 to August 31, 2026, is to enhance statistical methods for analyzing temporally observed, multi-sample data in fields such as environmental science, epidemiology, and economics. The research team will develop innovative approaches to estimate and infer trends in data...
This National Science Foundation (NSF) Project Grant award for $106,291, under the Mathematical and Physical Sciences program (CFDA 47.049), will support research to extend classical extreme value theory to models with interdependent numerical values and mean-field interaction. The project aims to study the convergence of upper and intermediate order statistics of certain systems of stochastic differential equations as their size grows, with applications in finance, medicine, and other...