This National Science Foundation Project Grant of $568,493 will support research at Northwestern University from April 1, 2022 to March 31, 2027 under the Engineering (47.041) federal grant program. The research will develop a comprehensive theoretical framework for analyzing rare catastrophic events driven by heavy-tailed distributions, which can model disparate phenomena like pandemics, blackouts, and financial crises. The framework will extend techniques in extreme value theory, optimization,...
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 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...
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, titled "COLLABORATIVE RESEARCH: LEARNING AND FORECASTING HIGH-DIMENSIONAL EXTREMES: SPARSITY, CAUSALITY, PRIVACY," aims to develop new statistical methods for forecasting extreme events and assessing their impacts. The $200,000 award to Cornell University, valid from August 15, 2023 to July 31, 2026, seeks to address challenges in analyzing high-dimensional, contaminated data to extract key features...
This $250,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports the development of algorithms for real-time dynamic risk identification and monitoring of streaming data, particularly in the domains of electronic medical records, mobile health, and supply chain. The key objectives are to create a unified framework for dynamic risk detection that can be incorporated into...
This $350,000 Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research to develop cost-efficient and confidence-building sampling methods for modern scientific discovery. The award to the Illinois Institute of Technology (IIT) aims to create a framework featuring new methodologies, theory, and algorithms that extend classical low-discrepancy sampling...
The National Science Foundation (NSF) awarded a $219,268 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of Chicago. The grant, effective July 1, 2024 through June 30, 2027, will support collaborative research on "Statistical Inference for High Dimensional and High Frequency Data: Contiguity, Matrix Decompositions, Uncertainty Quantification." The research aims to develop advanced mathematical and statistical methodologies to extract...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $199,961 Project Grant to North Carolina State University to develop a synergistic framework for accurate and real-time prediction of rare extreme events using observational data and mathematical models. The grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), aims to increase the accuracy of extreme event predictions while reducing computational costs to enable real-time...
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...