Project Grant 2319449
- 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...
- The National Science Foundation (NSF) awarded a $593,662 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Maryland, College Park. The grant supports the development of an asynchronous distributed machine learning framework for collaborative analysis of brain imaging and genomics big data across multiple research sites. Key objectives include: 1) designing new asynchronous distributed algorithms for genome-wide association studies and...
- This four-year Project Grant, awarded August 1, 2025, by the National Science Foundation's Division of Information and Intelligent Systems under the Computer and Information Science and Engineering program (CFDA 47.070), provides $400,000 in funding to Emory University to advance Graph Neural Network (GNN) technology through data-centric optimization strategies. The project will deliver research outcomes and methodologies addressing three critical GNN limitations: scalability, generalization...
- The National Science Foundation Division of Information and Intelligent Systems awarded a $143,624 Project Grant to the University of Georgia Research Foundation, Inc. under the Computer and Information Science and Engineering federal grant program (CFDA 47.070). The award will support a collaborative research project between multidisciplinary investigators to leverage advances in neuroscience data and develop brain-inspired artificial intelligence. Specifically, the researchers will analyze...
- 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 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 $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 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 three-year, $300,000 Project Grant from the National Science Foundation Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) will support the development of statistical methods for learning the evolution of connectivity in complex time series data. Key products include estimation and inference methods for a Nonstationary Graphical Model framework called NonSTGM that captures nonstationary dynamics in multivariate systems through a sparse...
- This $266,538 Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports collaborative research on the effects of connectivity architecture and distributed delays in brain network dynamics. The project aims to establish a quantitative framework that considers both spatial connectivity and temporal history of neural interactions, using networks of coupled equations with time delays. The research team, led by The Research...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program provides $200,000 to Emory University to develop new methods for modeling the dynamics of brain graphs derived from neuroimaging data. The 3-year project, starting on October 1, 2023, aims to create a unified framework of brain graph ordinary differential equations (BrainGDE) that integrates advanced deep graph learning techniques and ordinary differential equations. The research tasks focus on unimodal and multimodal dynamic brain graph mining, as well as clinical investigations in collaboration with domain experts. If successful, this work will reshape deep learning approaches for temporal data mining in bioinformatics and healthcare technologies, and establish a universal benchmark for future research on dynamic data with structural properties. This award reflects NSF's mission to advance scientific progress and technological innovation in computing and information science.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $200.0k | 9/14/23 |