Project Grant 2316235
Award Date
8/1/23
Completion Date
7/31/28
Dollars Obligated
$330K
Funding Federal Agency
Division of Information and Intelligent Systems
Awarding Federal Agency
Division of Computing and Communication Foundations
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Cambridge, MA 02139, USA
Similar Awards
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 $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research to develop a mathematical foundation for using graph data in machine learning. The key goals are to: 1) characterize how the geometry of the underlying latent space affects graph structure, 2) devise optimal algorithms for recovering latent feature vectors from observed graphs, and 3) find computationally efficient...
This $568,008 Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will support research to develop novel computational approaches for processing graph-structured data. The key activities include: Designing a scalable non-canonical representation to express graphs as combinations of intersecting cliques or communities, enabling efficient data processing algorithms for very large graphs like social...
This Project Grant award, provided by the National Science Foundation (NSF) Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), seeks to accelerate the execution of large graph problems on large, distributed machines. The $327,975 award to the Trustees of Indiana University, doing business as Indiana University, will fund a collaborative research effort across three interdependent main thrusts: new algorithms for graph...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award provides $364,000.00 to the Massachusetts Institute of Technology (MIT) from October 1, 2024 to September 30, 2028. The project aims to develop scalable, high-performance graph-based clustering algorithms capable of efficiently processing massive datasets with billions of entities. Key objectives include creating new algorithms for graph clustering and...
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 $255,353 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support research at Northeastern University focused on advancing sublinear-time graph algorithms. The key objectives of the 5-year project include developing more efficient sublinear-time algorithms for foundational graph problems, investigating the limitations of these algorithms through query lower bounds, and exploring connections...
This Project Grant award under the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of general algorithmic frameworks and frameworks for analyzing and manipulating various types of real-world networks, such as gene regulatory networks, brain networks, and online social networks. The $320,000 award to the Massachusetts Institute of Technology (MIT) will fund research to create provably-efficient...
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 the development of new methods for analyzing, generating, and optimizing graph-structured data. The research aims to create more expressive and efficient graph neural network models, improve generative models for graphs, apply graph learning techniques to optimization problems, and explore the use of graph neural networks for...
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...