The National Science Foundation (NSF) awarded a $299,973 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the Rector & Visitors Of The University Of Virginia (UVA), doing business as University of Virginia. The grant, titled "COLLABORATIVE RESEARCH: OAC CORE: DISTRIBUTED GRAPH LEARNING CYBERINFRASTRUCTURE FOR LARGE-SCALE SPATIOTEMPORAL PREDICTION", aims to develop a comprehensive set of graph construction and...
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...
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 National Science Foundation Project Grant award under the Social, Behavioral, and Economic Sciences program (CFDA 47.075) provides $349,984 to The Washington University in University City, Missouri to develop innovative computational and statistical methods for quantile regression analysis of big data. The key products and services to be delivered through this 3-year award include: An efficient online framework for quantile regression analysis of data streams to enable cost-effective,...
This $299,999 National Science Foundation Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) funds research into distance-based statistical methods for analyzing complex, high-dimensional data. The Washington University is the primary awardee, with work conducted from Oct. 2021 through Jun. 2024. The University of Pennsylvania serves as a subawardee, contributing to study design, implementation, analysis and manuscripts through the work of Dr. Bhaswar B....
The National Science Foundation (NSF) awarded a $179,055 Project Grant to the University of Virginia under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports collaborative research to develop privacy-preserving algorithms for fundamental problems in graph mining and network science. The project aims to create scalable, accurate graph differential privacy algorithms for applications like healthcare, social networks, finance, and computational...
The National Science Foundation (NSF) awarded a $600,000 Project Grant under the Computer and Information Science and Engineering (CFDA #47.070) program to the University of Utah Office of Sponsored Projects Division. The grant, awarded on June 15, 2023, will fund a project to build a foundational model for human mobility that can incorporate diverse types of movement, temporal, and socio-demographic data. The model will utilize machine learning techniques to generate outputs relevant to both...
The National Science Foundation awarded a $500,000 Project Grant to the George Washington University under the Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support research into the holistic design of high-performance and energy-efficient accelerators for graph neural networks from October 1, 2021 through September 30, 2024. As described under the CFDA program, funding will advance the development of computing and communications...
This $400,000 National Science Foundation Project Grant, awarded under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of statistical methods and machine learning techniques for analyzing complex structured and count data. Over a three-year period ending in August 2025, the University of Washington will advance the state of knowledge in big structured and count data analysis through two tracks of research. The first track will focus on revising and...
This $139,660 federal Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program. The grant supports research at the College of William and Mary to develop novel online data mining algorithms that can provide transparent and interpretable machine learning models for real-time applications such as crowd movement prediction, disaster monitoring, and pandemic response. Key objectives include: 1)...