This Project Grant award from the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083) provides $1,281,509 to the University of Illinois Chicago (UIC) to acquire a GPU cluster for accelerating HIPAA-compliant, data-driven artificial intelligence (AI) research in healthcare. The GPU cluster will enable UIC researchers to develop and use computationally-intensive AI models for a variety of health-related research projects and applications, including knowledge extraction...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop strategies for efficiently leveraging idle resources in high-performance computing (HPC) systems to accelerate large-scale artificial intelligence (AI) workloads. The key objectives are to: 1) analyze patterns of idle resources in HPC environments, 2) develop methods to safely and rapidly harvest these idle resources, and...
This $134,992 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research at Rensselaer Polytechnic Institute (RPI) to develop energy-efficient and scalable artificial intelligence (AI) systems. The key objectives are to: Leverage dynamic connectivity in AI models to reduce redundancy and adapt to specific tasks and data. Explore heterogeneous architectures integrating approximate, analog, and...
This National Science Foundation (NSF) Innovations of Graduate Education (IGE) Track 2 award to the University of Chicago will support the development of a data science (DS) and artificial intelligence (AI) credential program for STEM doctoral students. The $789,218 grant, effective from October 1, 2024 to September 30, 2029, will enable STEM doctoral students to learn how to apply DS and AI concepts in their respective disciplines, such as astrophysics, geophysical sciences, genetics,...
This $300,000 Project Grant awarded by the National Science Foundation's Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Massachusetts Institute of Technology (MIT) will support the development of advanced machine learning (ML) algorithms and data compression techniques to address the 200 TB/s data rate challenge for the LHCb Upgrade II experiment at CERN's Large Hadron Collider. Specifically, the project will extend the functionality of the HLS4ML software...
This $131,959 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research conducted by Rutgers, The State University to develop new deep learning training methods that can efficiently scale to utilize high-performance computing (HPC) systems. The key goals are to: 1) Explore techniques like second-order information approximation, computation-communication tradeoffs, and data compression to enhance the speed...
This $1,090,678 Project Grant awarded by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program supports research to develop computational algorithms that align deep neural networks (DNNs) with human visual processing. The project aims to rectify the growing "misalignment" between the behavior of large-scale DNNs and human cognition as AI systems become more capable. Researchers at Brown University will combine human...
This three-year, $651,130 National Science Foundation Project Grant will support the development of Pathoradi, an interactive web server for artificial intelligence-assisted radiologic-pathologic image analysis, correlation and visualization at Howard University. The server aims to address current challenges in comparing radiologic and pathologic images through three components: deep learning algorithms for quantifying cell morphological phenotypes in whole brain sections, a graphical and...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to advance the efficiency and productivity of high-performance computing (HPC) systems by leveraging idle resources to expedite artificial intelligence (AI) workload processing. The research project, conducted by the Trustees of the Stevens Institute of Technology, will analyze idle resource patterns in HPC environments, develop methods...
This Project Grant award from the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program will develop generative AI models to efficiently simulate high-energy particle interactions, enabling faster and more accurate particle tracking. The $491,530 award to the University of Wisconsin System will be used to create graph-based AI models that can accurately capture the complex, tree-like structure of particle showers following...