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 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...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $200,000 Project Grant to Texas A&M University to develop statistical modeling techniques for analyzing spatial-temporal human mobility flows from aggregated mobile phone data. The 3-year project aims to study community detection problems in origin-destination flow networks, with a focus on asymmetric flows and evolving community structures. The effort will involve developing Bayesian random graph partition...
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...
The National Science Foundation (NSF) awarded a $100,000 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to the University of Texas at Dallas (UTD) for the project "Predictive Anomaly Detection for Spatio-Temporal Data with Multidimensional Persistence". The project aims to develop novel machine learning and topological data analysis techniques to model spatial and temporal interdependencies in large spatio-temporal datasets, with applications in...
This $399,574 Project Grant awarded by the National Science Foundation's (NSF) Social, Behavioral, and Economic Sciences (CFDA 47.075) program supports research to assess and mitigate spatial biases in large-scale mobile location data used for human mobility analysis. The University of Florida, the prime awardee, will undertake four key research tasks: 1) quantify spatial bias in mobile location data; 2) identify causes of spatial biases from the data generation process; 3) develop new methods...
This $330,000 Project Grant award was provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049). The project will develop new AI-based techniques to detect anomalous behavior of individuals and groups based on their GPS location data. The investigators will create a temporal graph neural network (GNN) to characterize normal and abnormal location behavior patterns, and a dynamic graph anomaly detection (DGAD) approach to...
The National Science Foundation (NSF) awarded a $307,284 Project Grant under the Social, Behavioral, and Economic Sciences (CFDA 47.075) program to Regents of the University of Michigan Office of Research and Sponsored Projects (doing business as University of Michigan) to conduct a collaborative research study titled "HNDS-R: Stepping Out of Flatland: Complex Networks, Topological Data Analysis, and the Progress of Science." The 3-year project, beginning September 1, 2023, will use...
Iowa State University will receive $218,212 under a two-year National Science Foundation Project Grant in the Computer and Information Science and Engineering program to develop a sub-millisecond topological feature extractor for high-rate machine learning. The university will investigate real-time topological data analysis capabilities by developing advances in mathematical, software, and hardware foundations to enable integration of topological data analysis with machine learning for...
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,...