This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Program (CFDA 47.070) provides $300,000 to the Regents of the University of California at Riverside to conduct research on adapting foundation models for multimodal sequential decision-making. The project aims to develop novel techniques and methods to leverage foundation models, which are complex neural networks trained on large datasets, to improve the performance of...
The National Science Foundation (NSF) awarded a $200,000 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to Virginia Polytechnic Institute & State University (Virginia Tech) for the project "Towards Large Open-World Foundation Models: Construction, Adaptation, and Deployment." This 3-year project, with an end date of July 31, 2028, aims to develop new algorithms, theorems, and systems to ensure the reliability of advanced...
This $333,000 Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program supports the development of a novel neurosymbolic programming framework called "Foundation Model Programming." The project aims to enable the generation of symbolically interpretable scientific hypotheses from high-dimensional observational data, such as images and videos, across domains like neuroscience, genomics, and ecology. The framework will...
This $333,667 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program will support the development of a novel neurosymbolic programming framework called "Foundation Model Programming." This framework aims to generate symbolically interpretable scientific hypotheses from high-dimensional observational data across disciplines such as neuroscience, genomics, biomechanics, and ecology. The key objectives are to create...
This Project Grant award of $300,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program supports research on developing machine learning models for structural decision-making. The goal is to create models that can capture an agent's preferences and understanding of environmental dynamics, enabling better prediction and adaptation of decision-making in complex real-world scenarios. The research will explore methods for...
This $948,000 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) will support the development of new methods for data-efficient decision-focused learning to address uncertainty in various real-world decision-making problems. The research aims to create a general framework for pre-training key components and rapidly fine-tuning them for specific decision-making tasks, such as in public health,...
This Project Grant award of $300,000 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research by the Texas A&M Engineering Experiment Station (Tees) to develop machine learning models for learning structural frameworks of an agent's dynamic decision-making behavior. The project aims to advance state-of-the-art methodologies for learning structural models of control by considering diverse data types, including...
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 $299,977 federal Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) aims to develop AI-powered approaches to address challenging societal problems in the areas of drought resilience, emissions reduction, and infectious disease response. The overarching goal is to establish theoretical and algorithmic foundations for responsible and equitable AI-powered sequential, collective decision-making. The...
This Project Grant award, provided by the National Science Foundation (NSF) under the Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), aims to develop a novel neurosymbolic programming framework called "Foundation Model Programming." This framework is designed to generate symbolically interpretable scientific hypotheses from high-dimensional observational data, such as images and videos, across various scientific disciplines like...