This Project Grant award of $355,999, made by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports the development of a new highly parallel hardware and software system called PANTHER. This system is designed to simultaneously support large language models (LLMs) and large-scale graph computations, in order to improve the reliability and efficiency of modern artificial intelligence (AI) techniques. The research aims to...
This Project Grant award of $360,000.00 from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the Massachusetts Institute of Technology (MIT) aims to develop new methods for efficient, architecture-aware algorithms for large language models (LLMs). The goals are to make existing LLM applications more efficient, enable new applications, and broaden access to this transformative AI technology. The key focus areas include: (1)...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program aims to advance artificial intelligence (AI) by investigating the mathematical foundations and practical applications of deep learning models. The $600,000 award, with a performance period from December 2024 to November 2027, will support research focused on understanding the properties of neural networks, the function spaces and data representations that emerge...
This $300,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to improve the evaluation and functionality of large language models (LLMs). The University of Texas at Austin will lead this 3-year collaborative research project to identify a taxonomy of "evaluation concepts" for assessing LLM responses and develop technology to automatically evaluate and improve LLM performance based on...
The National Science Foundation (NSF) awarded a $292,237 Project Grant under the Computer and Information Science and Engineering (CISE) program to the University of Illinois. The grant, titled "A Framework to Power Next-Generation AI-Based Scientific Models on Hardware with Massive Parallelism," aims to address two key challenges faced by non-computer science researchers in utilizing modern hardware with massive parallelism for training advanced AI models for scientific discovery. The...
This Project Grant award, funded by the National Science Foundation's (NSF) Integrative Activities program (CFDA 47.083), will support the development of a specialized artificial intelligence (AI) foundation model for planning-like tasks. The $150,000 award, effective from February 1, 2025 to January 31, 2027, aims to create a compact and comprehensive AI model that can outperform and be more efficient at tasks requiring sequential decision-making, reasoning, and planning compared to the current...
This $400,000 Project Grant was awarded on July 1, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) to the Regents of the University of Michigan to conduct collaborative research on the theoretical foundations of compositional learning in large language models based on transformer architectures. The research aims to investigate three key areas: model expressivity, statistical learning theory, and optimization, with...
This $557,460 National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program Project Grant, awarded on October 1, 2025, supports the development of a new AI framework for real-time, scalable, and verifiable generative video editing. The key innovations include motion-adaptive cross-frame attention, pipelined frame scheduling for multi-GPU systems, formal verification of semantic consistency, and system-level validation on real hardware. These advancements aim...
This Project Grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), will fund research to better understand the differences between how humans and AI language models process and interpret language. The $432,656 award to the University of Massachusetts (UMass) will explore techniques to align AI models more closely with human language comprehension, including investigating the relationship between model...
This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) federal grant award to the University of Texas at Austin is for the "COLLABORATIVE RESEARCH: FRAMEWORKS: HPCGPT: ENHANCING COMPUTING CENTER USER SUPPORT WITH HPC-ENRICHED GENERATIVE AI" project. The $357,359 award, which runs from August 1, 2024 to July 31, 2027, will fund the development of an AI-powered question answering service called HPCGPT to enhance the user support capabilities at...