This federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $316,000 in funding to The Leland Stanford Junior University (Stanford University) to develop a general foundation model framework for scientific discovery using graph-structured data. The research aims to address key limitations in existing graph foundation models, such as the inability to handle complex graph structures or...
This $600,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) is focused on enhancing machine learning with graph-structured data. The research aims to address the challenge of data distribution shifts in AI models when applied to real-world scenarios, particularly in fields like particle physics and biochemistry. The key activities under this 3-year award include: Developing methods to estimate and...
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 Project Grant award of $600,000 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports research at the Massachusetts Institute of Technology (MIT) to develop a mathematical foundation for using graph data in machine learning tasks. The goal is to create principled methods for exploiting the latent geometry and structure underlying graph data, such as from social networks or protein interaction networks, to improve machine learning...
The National Science Foundation awarded a $499,979 project grant to the George Washington University under the Computer and Information Science and Engineering program (CFDA 47.070). The grant will support research towards developing high-performance machine learning techniques on graphs from October 1, 2021 to September 30, 2024. The Computer and Information Science and Engineering program aims to advance computing and informatics research and education. This award will further those goals by...
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 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $160,338 to the Illinois Institute of Technology (IIT) to develop new methods for analyzing, generating, and optimizing graph-structured data. The 3-year project aims to advance graph neural network models and their applications in areas such as social network analysis, molecular design, and physical systems modeling. Key research thrusts...
The National Science Foundation (NSF) awarded a $498,229 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to Yale University. The grant will fund research to develop new mathematical and machine learning techniques for analyzing complex, high-dimensional biomedical data such as single-cell sequencing and gene regulatory networks. Key research thrusts include creating data geometric features and neural network models to characterize point cloud data, preserving...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program, with a CFDA number of 47.070, provides $557,158 to the University of Connecticut (UConn) from March 1, 2025 to February 29, 2028. The project aims to devise novel mathematical operators that address performance bottlenecks in graph-based AI applications, such as autonomous systems, traffic forecasting, and semiconductor chip design. The research will focus on...
This $599,573 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports the University of Notre Dame's research to develop a new machine learning paradigm for effective yet efficient foundation graph learning models (FGLMs). The project aims to create techniques, methods, and models for FGLMs that can be widely applied in areas like scientific research, social network analysis, anomaly detection, drug...