Project Grant 2427965

Award Date 10/1/25
Completion Date 9/30/28
Dollars Obligated $287K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Newark, DE 19716, USA
Similar Awards
This three-year, $345,853 project grant from the National Science Foundation's Division of Computing and Communication Foundations will support the development of a new hypergraph signal processing framework via tensor representations. Funded under the Computer and Information Science and Engineering program, the collaborative research aims to advance tools for exploiting multi-way interactions in complex data using hypergraphs rather than solely pairwise relationships as in simple graphs....
This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) provides funding of $238,061 to the University of Delaware from August 15, 2024 to July 31, 2027. The award supports the Principal Investigator's research to develop a systematic mathematical approach for analyzing and visualizing large complex networks, such as social networks, biological networks, and neural cell networks. The key research objectives include...
This $360,000 National Science Foundation project grant supports research to advance graph signal processing techniques for electric power distribution system monitoring and control from July 2022 through June 2025. Funded under the NSF Engineering program (CFDA 47.041), the awardee Cornell University will develop a novel mathematical approach incorporating physical grid modeling into machine learning algorithms. The approach interprets system states as graph signals to extract features...
This federal Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE, CFDA 47.070) program provides $300,000 to Northeastern University to develop a novel approach called "Graphides" for analyzing and predicting phenomena using sparse graph data. The project aims to establish a rigorous theoretical framework for studying the limits and properties of sparse random graph models, with applications in areas such as...
This Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will develop general algorithmic frameworks and analysis tools for understanding and manipulating real-world networks across various domains. The $300,000 award to the University of Maryland, College Park, with a period of performance from April 2024 to March 2027, aims to create provably efficient algorithms that can provide quality...
The National Science Foundation (NSF) awarded a $484,822 Project Grant through its Computer and Information Science and Engineering (CFDA #47.070) program to the University of Chicago. This 5-year grant, effective July 1, 2023, supports research into characterizing the properties, reliability, and sensitivity of graph neural networks (GNNs) and advancing the theoretical understanding of statistical properties in graph estimators. The goal is to transform GNNs from black-box models into...
The National Science Foundation Division of Electrical, Communications and Cyber Systems awarded a $299,999 Project Grant to the University of California, Davis to support research titled "CCSS: HYPER-GRAPH SIGNAL PROCESSING FOR MULTIMEDIA DATA ANALYSIS IN CYBER SYSTEM APPLICATIONS." The three-year award, issued on June 1, 2021 with a completion date of May 31, 2024, will fund the development of hyper-graph signal processing techniques to enable advanced analysis of multimedia data...
This $150,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports collaborative research to develop new methods for analyzing, generating, and optimizing graph-structured data. The project aims to create more expressive and efficient graph neural network models, improved generative models for graphs, and apply graph learning techniques to optimization problems and physical systems modeling. The...
This $255,353 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) Project Grant awarded to Northeastern University will fund research on sublinear-time graph algorithms. The project aims to develop more efficient and optimal sublinear-time algorithms for foundational graph problems, understand the limitations of these algorithms through query lower bound analysis, and explore connections to other computation models like dynamic, parallel, and...
This Project Grant award of $200,000.00 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) will support research at the New Jersey Institute of Technology (NJIT) to develop novel techniques for analyzing spatial-temporal data in AI of Things (AIoT) systems. The research project aims to advance graph signal processing and graph learning methods to enable interpretable and efficient analysis of complex,...

This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, CFDA 47.070, provides $287,125 to the University of Delaware to develop theoretical foundations for robust signal processing on spatial networks. The project aims to leverage techniques from harmonic analysis, functional analysis, and graph-limit theory to address challenges in information processing, particularly in the theoretical underpinning of graph signal processing (GSP). The goal is to develop a theory applicable to a wide range of large dynamic networks, including those modeling social media, sensor grids, and brain connectivity. The award supports graduate student mentoring, scientific workshops, and outreach activities. The project period runs from October 1, 2025 to September 30, 2028.

Generated 8/5/25, 5:11 AM