Project Grant 2443877
Award Date
9/1/25
Completion Date
8/31/30
Dollars Obligated
$500K
Federal Agency
Division of Information and Intelligent Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Fayetteville, AR 72701, USA
Similar Awards
This $400,000 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 a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models. The key objectives are to: 1) create new methodologies to visualize the internal mechanisms and hierarchical structures of pre-trained multimodal generative models, 2) explore model...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop a hybrid, vision-centric framework that integrates intuitive and deliberate visual processing to create more robust visual intelligence. The $111,878 award to New York University (NYU) supports research focused on advancing vision-centric parametric knowledge, incorporating human-like non-parametric mechanisms, and integrating these...
This Project Grant award of $660,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to advance multi-stream architectures for computer vision and other multi-modal artificial intelligence applications. The project aims to: (1) develop a suite of high-performance multi-stream foundation models for tasks like object detection, text-based image segmentation, and audio-video analysis; (2) create optimized algorithms to...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program, with a total funding amount of $584,034, supports research to improve the interpretability of machine learning models in computer vision. The project aims to develop new technologies that allow machine learning-based computer vision models to explain their reasoning processes to human users and enable users to interact with the models to correct mistakes. Key...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $496,895 over a 3-year period starting September 1, 2024 to develop a unified framework for simplifying and automating the development, optimization, and adaptation of video analytics pipeline (VAP) applications. The key products and services to be delivered under this grant include: A framework that enables domain experts to specify...
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 National Science Foundation (NSF) Project Grant award under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) provides $400,000.00 to the University of California, Berkeley (UC Berkeley) to conduct research on understanding, visualizing, and attributing multimodal generative models - large-scale AI models that generate both text and images. The research aims to develop new systematic frameworks for analyzing the internal mechanisms and...
This $400,000 Project Grant award was provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) Federal Grant Program. The project aims to develop a systematic framework for visualizing, understanding, and rewriting the learned computations of multimodal generative AI models, in order to increase the accountable and safe use of these advanced AI systems and mitigate potential harms. The key research thrusts involve: 1) new...
The National Science Foundation (NSF) Division of Information and Intelligent Systems awarded a $600,000 Project Grant to the University of California, San Diego (UCSD) under the Computer and Information Science and Engineering (CFDA 47.070) program. The 3-year grant, effective July 1, 2023, supports research to develop dynamic neural network architectures that can efficiently enable multimodal perception, including vision, audio, and language processing. The research aims to address...
This Project Grant award of $174,965, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CFDA 47.070) program, supports the development of an evidence-aided symbolic reasoning framework to enable trustworthy multi-modal, multi-agent machine learning (ML) systems. The key products and services to be delivered include: 1) Investigating evidence theory to develop trust metrics for assessing ML pipeline decisions and uncertainty; 2) Creating...