This three-year project grant from the National Science Foundation's Mathematical and Physical Sciences program, totaling $359,940, will support the development of new statistical models and algorithms for analyzing large, spatially-dependent data sets collected from complex domains with irregular boundaries. Specifically, the awardee, Texas A&M University, will introduce a class of nonstationary models that can flexibly characterize potentially heterogeneous spatial dependence while...
The National Science Foundation (NSF) awarded a $200,000 Project Grant to Iowa State University of Science and Technology to develop new algorithms and a toolkit for analyzing spatiotemporal datasets to better understand human behavior and mobility patterns. The 3-year project, funded under the NSF Mathematical and Physical Sciences program (CFDA 47.049), aims to combine topological data analysis and time-frequency analysis to detect anomalies in datasets like volumetric traffic data and U.S....
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) aims to revolutionize the understanding and prediction of human mobility patterns. The $300,000 award to Lehigh University, to be executed from September 1, 2024 to August 31, 2027, will support the development of privacy-preserving, federated neural networks to analyze large-scale, cross-domain human mobility data from sources like smartphones, payment...
This $350,000 National Science Foundation project grant supports statistical modeling research for complex networks at the University of Michigan from September 2022 through August 2025. Funded through the NSF's Mathematical and Physical Sciences program (CFDA 47.049), the award aims to develop new statistical methodologies and theory to incorporate higher-order structures into network modeling. Specifically, the investigators will study leveraging subgraphs and other higher-order structures...
The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA #47.070) program to the University of Utah Office of Sponsored Projects Division. The grant, awarded on June 15, 2023, will fund a project to build a foundational model for human mobility that can incorporate diverse types of movement, temporal, and socio-demographic data. The model will utilize machine learning techniques to generate outputs relevant to both...
This $249,358 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports research by Amherst College on non-local microscopic and macroscopic traffic flow models. The investigator will construct and analyze multi-scale non-local mathematical models to more accurately capture driver behavior by integrating downstream information, compared to traditional local traffic flow models. The project aims to perform mathematical...
The National Science Foundation Division of Mathematical Sciences awarded $249,814 under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program to the Research Foundation of the City University of New York to analyze random structures and stochastic dynamics arising across scientific disciplines. The three-year project grant will support theoretical and empirical analysis of spatial and non-spatial random graph models, stochastic processes on graphs, and network-based...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $255,000 Project Grant to the University of Florida (UF) under the Mathematical and Physical Sciences program (CFDA 47.049) to develop geospatial modeling and risk mitigation tools for hurricane evacuation and disaster response. The 3-year project leverages human mobility data from mobile devices and vehicle traffic monitoring to build statistical and optimization models that can improve the efficacy of disaster...
This $275,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program will support collaborative research to develop new statistical approaches for comparing and aligning networks. The research will focus on investigating optimal transport-based distances for Markov embeddings of networks, developing new methods for network alignment and comparison, and establishing theoretical results about these approaches. The...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a 3-year, $100,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to Rutgers, The State University located in New Brunswick, New Jersey. The grant supports the development of advanced statistical models and software to predict and assess the likelihood of extreme geopolitical events with quantified uncertainty. The project aims to construct a comprehensive, data-driven prediction...