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) Project Grant, awarded under the Computer and Information Science and Engineering program (CFDA 47.070), provides $220,000 to Yale University from September 1, 2023 through August 31, 2027. The project aims to develop a smarter artificial intelligence (AI) system to better understand and analyze complex medical images, such as those from multiple scans of a patient. The research team will tackle challenges to make the AI system more scalable, interpretable,...
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 $317,591 federal Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to enhance personalized healthcare through the use of large language models (LLMs) and novel memory semiconductor devices. The project aims to develop efficient retrieval-augmented generation (RAG) techniques for LLM personalization, focusing on reducing latency and hardware overhead through algorithm-hardware...
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,...
This $347,570 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop a comprehensive Knowledge Graphs-Large Language Model Co-Learning (KG-LLM Co-Learning) framework for enhancing the performance and reliability of large language models in healthcare applications. The research team at Emory University will focus on three key innovations: 1) constructing comprehensive healthcare knowledge...
This $256,260 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 the development of a rigorous mathematical framework to understand the effectiveness of diffusion models, a key component of the recent revolution in generative artificial intelligence (AI). The project aims to advance machine learning theory by providing new definitions and algorithmic goals for these...
This $207,737 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will fund research to develop a new class of machine learning models called "Programmatic Foundation Models" that can efficiently analyze large-scale satellite, aerial, and ground imagery. The goal is to create interpretable, robust AI models that can understand global and local phenomena from images, providing insights...
The National Science Foundation Division of Information and Intelligent Systems awarded Yale University $550,000.00 under the Computer and Information Science and Engineering federal grant program (CFDA 47.070) for the project "CAREER: FROM FAIRNESS TO JUSTICE IN AI SYSTEMS" from October 1, 2021 to September 30, 2026. This five-year project grant will support Yale University's investigator-initiated research and education efforts aimed at advancing the development of fair, just and...
The National Science Foundation (NSF) awarded a $597,893 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) program to the University of Connecticut (UConn). This 3-year grant, starting on May 1, 2024, is dedicated to developing novel algorithms and computational methods that integrate genomics, pathology, and other multimodal data to build precise disease prediction models. The project aims to advance the state-of-the-art in integrating diverse molecular data...
This federal Project Grant award of $240,000.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) is supporting research at Yale University to develop new computational frameworks that combine large language models with operator learning techniques. The goal is to address key challenges in modeling spatiotemporal phenomena in biomedical research, with applications in areas such as personalized medicine, disease modeling, and drug discovery. The research aims to create AI methods that can better track continuous changes in biological systems, build foundation models to handle diverse biomedical data, and develop specialized tools for gene expression analysis. These advancements are expected to improve the predictive power and interpretability of machine learning in healthcare contexts, leading to more accurate diagnoses, efficient drug development, and deeper understanding of cellular and brain processes. The award period runs from June 15, 2025 to May 31, 2030.