Project Grant 2318817
- The National Science Foundation awarded a $275,000 Project Grant to the University of Southern California under the Mathematical and Physical Sciences program (CFDA 47.049) from August 2023 through July 2026. The grant funds research to develop robust and scalable algorithms for learning hidden structures in sparse network data. The University of Southern California will conduct research to combine node-level side information with network interaction data to more effectively analyze network data...
- This $125,000 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports a collaborative research project on developing improved graph neural network (GNN) algorithms for threat detection. The key research objectives are to: 1) maintain accuracy with deep GNNs, 2) enable GNN training with limited data, and 3) reduce computational costs for training and deploying deep GNNs with...
- This Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences (CFDA 47.049 - Mathematical and Physical Sciences) supports research to develop novel mathematical models and efficient algorithms for deep learning on large-scale graph-structured data. The $249,999 award, spanning September 2024 to August 2027, aims to produce innovations in areas like graph convolutional networks, graph matching, and graph clustering. The research will involve graduate...
- This $229,461 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports the development and analysis of novel self-supervised probabilistic graph structure learning models. The goal is to uncover latent representations hidden within large datasets, which can provide valuable insights across diverse applications like cancer research and environmental analysis. The research will involve creating advanced mathematical models,...
- 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) Division of Mathematical Sciences awarded a $300,000 Project Grant to Trustees of Tufts College, doing business as Tufts University, to develop methods for representing, analyzing, and learning functions on heterogeneous graphs. The project, titled "Diffusion and Transport on Graphs: Active Learning, Low-Dimensional Representations, and Anomaly Detection," will focus on two interconnected settings: (i) semi-supervised learning of functions on a...
- This Project Grant award for $270,000.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports the development of advanced computational methods for tracking and analyzing evolving patterns in large-scale networks. The research will focus on three integrated thrusts: 1) creating novel algorithms with provable efficiency guarantees for counting and enumerating subgraphs in dynamic network models, 2) designing and implementing...
- This Project Grant award in the amount of $250,000 was provided by the National Science Foundation (NSF) under the Mathematical and Physical Sciences (CFDA 47.049) federal grant program. The funding will support research at Loyola Marymount University to develop advanced network analysis methods for studying the evolution of online social discourse and topic clusters in large-scale knowledge graphs. The project aims to create interpretable network-based similarity metrics and solvers that can...
- 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 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 $100,000 Project Grant awarded by the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) supports a research project by the University of California, Los Angeles (UCLA) to develop active learning algorithms for detecting patterns of activity in complex, multimodal data structures organized as multiplex networks. The project aims to address the challenge of extracting insights from large, heterogeneous datasets that may have hidden information, such as transportation networks, social media activity, and synthetic models of human behavior. The research will focus on subgraph matching problems, incorporating both exact and inexact matching approaches that consider factors like graph topology, timestamps, label attributes, and geographic information. The active learning techniques will involve collaboration with subject matter experts to navigate the complex solution space. The project is expected to run from Sep 1, 2023 to Aug 31, 2026.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $100.0k | 7/19/23 |