Project Grant 2323533
- This $270,000 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of advanced computational methods and software tools for tracking and analyzing evolving patterns in large-scale networks. The key objectives are to: 1) develop novel algorithms with provable efficiency guarantees for counting and enumerating network subgraphs, 2) design and implement high-level programming...
- This three-year, $532,241 Project Grant from the National Science Foundation's Division of Computer and Network Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of scalable algorithms, systems, and infrastructures for graph neural network training. The University of Massachusetts will develop a novel "split parallelism" training paradigm to transparently scale graph neural network training to large-scale graphs...
- This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070) supports a collaborative research effort to accelerate the execution of large-scale graph problems on distributed computing systems. The $2,656,268 award, active from August 1, 2023 to July 31, 2028, aims to develop new algorithms, software frameworks, and hardware accelerators to efficiently process large graph datasets in domains like computational...
- This National Science Foundation (NSF) Project Grant award, under the STEM Education (CFDA 47.076) program, provides $150,000 in funding to Lehigh University for a collaborative research project titled "DYNAMIC BRAIN GRAPH MINING - MAPPING THE CONNECTIONS IN HUMAN BRAINS AS NETWORKED SYSTEMS." The project aims to develop new methods for modeling the dynamics of brain graphs derived from neuroimaging data, in order to generate accurate, interpretable, and fair predictions about...
- This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program provides $270,000 to Yale University to develop advanced computational methods for analyzing evolving patterns in large-scale networks. The project will pursue three main research thrusts: (1) creating novel, efficient algorithms for counting and enumerating network subgraphs; (2) designing high-level programming frameworks and data structures...
- This $314,283 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, awarded on June 15, 2025, supports research by Mississippi State University to develop a unified framework for analyzing general graph dynamics and interconnected networks. The key objectives are to: 1) Develop a theoretical framework using advanced methods to derive a generalized, interpretable model for graph dynamics; 2) Create computational...
- This $1,091,988 federal Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports the development of a new framework to systematically design and optimize high-performance graph analytics algorithms. The researchers at the University of California, Davis (UC Davis) will create an open-source software platform that allows for automated exploration of implementation choices for graph computations using a...
- 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 federal Project Grant award, funded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support the development of new community detection methods and software capable of analyzing large networks with millions or billions of vertices. The $398,000 award to the University of Illinois will enable the creation of highly efficient parallel algorithms and software implementations that can be deployed on high-performance...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) project grant awards $600,000 to the Rector & Visitors of the University of Virginia (University of Virginia) to develop innovative approaches for efficient training of Dynamic Graph Neural Network (DGNN) models on large-scale, time-varying graphs. The 3-year project, from October 2024 to September 2027, aims to create novel methods for graph partitioning, sampling, caching,...
This National Science Foundation project grant of $225,884 awarded on March 15, 2023 will fund the development of fast and scalable algorithms for mining and analyzing large dynamic graphs. Under the Integrative Activities program (CFDA 47.083), which enhances STEM competitiveness through capacity building and infrastructure development, this University of Nevada, Las Vegas project will generate new algorithmic techniques and scalable software tools. Specifically, the awardee will design parallel methods with efficient load balancing and communication avoidance to reveal dynamic behaviors in socio-technical systems like social networks and brain networks. The results have applications in domains including neuroscience, bioinformatics, and infrastructure. The project also aims to expand the awardee's research capacity and serve a diverse student population.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $225.9k | 3/21/23 |