This $149,999 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research on network analysis and optimal transport methods for Markov embeddings of networks. The research project, led by the University of North Carolina at Charlotte, aims to develop new statistical approaches for comparing and aligning networks, with applications in computational neuroscience, systems biology, and urban planning. The key products...
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...
This federal Project Grant award, funded by the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049), supports research to develop a systematic mathematical approach for analyzing and visualizing large networks. The Principal Investigator (PI) aims to integrate discrete mathematics and analysis to extract large-scale features of complex networks, with potential applications in areas such as data analysis in sociology, psychology, and image processing....
This $300,000 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) will fund research into spectral methods for single and multiple graph inference networks. The grantee, North Carolina State University, will develop efficient parameter estimation methods for latent position graphs and valid two-sample testing procedures for comparing latent position graphs while ignoring irrelevant features. The...
This Project Grant award, with a total funding amount of $150,000.00, was provided by the National Science Foundation's (NSF) Division of Mathematical Sciences under the CFDA program "Mathematical and Physical Sciences." The award aims to develop scalable subsampling algorithms for statistical inference on large-scale networks across scientific fields, including biological and social sciences. The project will investigate the theoretical properties of these subsampling methods to...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $250,000 Project Grant to the University of Central Florida (UCF) under the Mathematical and Physical Sciences program (CFDA 47.049). The three-year grant, effective August 1, 2023 through July 31, 2026, supports research to develop extensions and analytical techniques for Generalized Dot Product Graph (GDPG) network models, with a focus on applications in brain science, medical research, molecular biology,...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences (CFDA 47.049) program provides $300,000 over a 3-year period from August 2024 to July 2027 to the Regents of the University of Michigan to conduct research on the mathematical and computational modeling of networked systems. The key research areas include: 1) Creating accurate mathematical models of network structures to enable realistic simulations using limited data; 2) Developing...
This $180,000 Project Grant award from the National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) program supports the development of novel community detection tools and frameworks for analyzing weighted network data, with a focus on applications in bioinformatics and biological science. The primary goals are to identify highly correlated gene modules by leveraging covariance or correlation matrix representations, and to provide a systematic, computationally...
This National Science Foundation project grant of $164,006 awarded on March 1, 2023 will support research applying algebraic and topological methods in graph theory to complex network models throughout the sciences. Funded under the Mathematical and Physical Sciences program (CFDA 47.049), the award to Southern Illinois University Carbondale will advance understanding of quantitative graph measures and their structural properties. Researchers will develop graph invariants accounting for...
The National Science Foundation (NSF) awarded a $175,000 Project Grant under the Mathematical and Physical Sciences (MPS) program to North Carolina State University (NC State) for the project "Scalable and Generalizable Inference for Network Data". The project aims to advance the statistical analysis of complex digital networks by addressing challenges in accurately reflecting network realities and efficiently managing their vast scales. Key products and services to be delivered...