This Project Grant award from the National Science Foundation (NSF) Office of Advanced Cyberinfrastructure, through the Computer and Information Science and Engineering (CFDA 47.070) program, provides $333,621.00 to Boise State University for a collaborative research project focused on training users, developers, and instructors at the chemistry/physics/materials science interface. The project aims to establish a robust community of materials modeling developers and enhance computational...
The National Science Foundation (NSF) awarded a $250,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Virginia. The grant supports the development of new physics-guided graph network models to capture complex, non-stationary, and poorly observed water dynamics in freshwater ecosystems. Key innovations include new graph-based architectures, continual learning strategies, and model initialization methods that leverage...
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 $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 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $631,953 to Yale University to develop a general foundation model framework for graph-structured data in scientific discovery. The researchers will address key limitations in existing graph foundation models by incorporating novel approaches such as multi-level graph neural networks, graph signal processing, multimodal graph...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Award (CFDA 47.070) in the amount of $314,283 provides funding to Mississippi State University to advance cross-graph dynamics and modeling of interconnected complex systems. The project aims to develop a unified computational framework to analyze shared behavioral patterns across diverse networked systems, such as transportation networks, power grids, and social platforms. Key objectives...
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 $557,158 Project Grant award, provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will support research to develop novel mathematical operators that address performance bottlenecks in graph-based AI applications. The goal is to enable efficient processing of large-scale graph data to improve the performance and scalability of emerging AI technologies, such as autonomous systems, traffic forecasting, drug discovery,...
The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to Arizona State University (ASU) to support research on linear and nonlinear diffusion, charge conductivity of proteins, and the polarity of electrified interfaces. The 3-year grant, running from June 1, 2025 to May 31, 2028, will enable Professor Dmitry Matyushov to develop theoretical models and computational algorithms to better understand the impact of...
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...