Project Grant 2341040
Award Date
8/1/24
Completion Date
7/31/29
Dollars Obligated
$250K
Federal Agency
Division of Information and Intelligent Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Los Angeles, CA 90095, USA
Similar Awards
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...
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 the development of a new framework and tools for advancing data-centric artificial intelligence (AI) through generative approaches to feature space reconstruction. The project aims to transform the traditional way of constructing feature spaces by using deep generative learning instead of manual or classical discrete search...
This $550,000 Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program supports the development of generative artificial intelligence (AI)-powered products that enable humans to interact and converse with books and other documents. The key products being developed include: Technology to represent the informational content of books and document discussions as a knowledge graph, which will then be used to ground large...
This $247,811 Project Grant award from the National Science Foundation (NSF) Engineering Directorate (CFDA 47.041) supports research at Oberlin College to develop and test AI programming tools to assist scientists in writing computer programs for scientific research. The goal is to create AI models and tools that can help scientists, who are not expert programmers, be more productive and improve the reproducibility of scientific work. Key products and services include developing large language...
This $352,236 National Science Foundation (NSF) Computer and Information Science and Engineering (CFDA 47.070) project grant was awarded to the Trustees of the Stevens Institute of Technology in Hoboken, New Jersey. The project aims to develop new structured generative modeling and learning frameworks to advance artificial intelligence (AI) for more informative, controllable, and cross-domain representations. Key technical objectives include creating context-aware generative models that...
This EAGER (Early-Concept Grants for Exploratory Research) award from the National Science Foundation's (NSF) Engineering program (CFDA 47.041) will develop generative artificial intelligence (AI) methods to learn from computational physics simulations and mathematical equations. The $300,000 project aims to expand the capabilities of large language models, such as OpenAI's ChatGPT and Microsoft's Copilot, to go beyond text-based learning and make predictions on complex, coupled physics problems...
This $399,162 Project Grant award from the National Science Foundation's Geosciences Program (CFDA 47.050) aims to develop interpretable, stable, and mass-conserving artificial intelligence (AI) models to improve the computational speed and efficiency of geoscientific models, such as those used for air pollution and climate research. The project will create simpler "surrogate" machine learning models for key components like atmospheric chemistry and wildfire plume rise, allowing for...
This $300,000 federal Project Grant award was provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) to the University of Maryland, College Park. The project aims to develop physics-guided generative artificial intelligence models to better understand and predict complex physical processes like pollution transport, virus spread, and wildfire evolution. By integrating physical equations with generative machine learning...
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...
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...