Project Grant 2404989
- Federal Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded $477,128 to the University of Arizona under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) on August 1, 2025, for a five-year CAREER project extending through July 31, 2030. The project delivers foundational research and practical algorithmic implementations in interactive machine learning (ML) with rich feedback modalities, addressing...
- The University of Arizona was awarded a $507,424 Project Grant from the National Science Foundation's (NSF) Computer and Information Science and Engineering program (CFDA 47.070). The three-year award will support the university's research project "SMALL: LEARNING TO CORRECT ERRORS" from October 1, 2021 through September 30, 2024. The NSF's Computer and Information Science and Engineering program aims to advance computing research and education. This award will fund the University of...
- This $300,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of next-generation mathematical and algorithmic tools to address two key issues in applying machine learning to statistical modeling of time-evolving complex systems: a shortage of informative training data and the high computational costs of high-dimensional problems. Specifically, the...
- The National Science Foundation Division of Mathematical Sciences awarded Texas A&M Engineering Experiment Station a $180,000 Project Grant under the Mathematical and Physical Sciences federal grant program (CFDA 47.049) from August 1, 2023 through July 31, 2026. The award will support research to develop a systematic approach for constructing deep Bayesian neural networks that are both computationally efficient and amenable to model designs. The research is expected to lead to...
- Federal Grant Award Summary The University of Arizona received a $250,000 collaborative research Project Grant from the National Science Foundation (NSF) Division of Electrical, Communications and Cyber Systems under the Engineering program (CFDA 47.041), effective October 1, 2025, through September 30, 2028. This award supports the development of efficient and scalable optimization algorithms for constrained, nonconvex bilevel optimization problems with applications in planning and control...
- This Project Grant award of $160,673 from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to combine algorithms and machine learning to improve decision-making under uncertainty. The project, led by New York University (NYU), will explore incorporating machine-learned predictions into algorithm design as well as developing learning models optimized for specific algorithmic objectives. This work aims to create a...
- This $229,461 Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports the development and analysis of novel self-supervised probabilistic graph structure learning models. The goal is to uncover latent representations hidden within large datasets, which can provide valuable insights across diverse applications like cancer research and environmental analysis. The research will involve creating advanced mathematical models,...
- The National Science Foundation (NSF) awarded a $187,593 Project Grant under the Mathematical and Physical Sciences (CFDA 47.049) program to the University of Arizona, doing business as the Arizona Board of Regents. This 3-year effort, starting on August 1, 2024, seeks to develop novel modeling and simulation approaches for complex material systems. Key objectives include: Utilizing machine learning, mathematical techniques, and physical principles to construct models that provide more realistic...
- This $994,988 National Science Foundation project grant through the Engineering program (CFDA 47.041) will fund research at the University of New Mexico from May 1, 2023 through April 30, 2028. The research aims to develop an algorithmic framework for integrating knowledge of human perception and reasoning about uncertainty into the design and control of autonomous dynamical systems. New mathematical theory and computational algorithms will be created based on control theory, machine learning,...
- This $271,343 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research into developing robust machine learning and inference methods that can withstand data corruption and distribution shifts. The project aims to explore new techniques for structured learning, supervised learning, and reinforcement learning that are resilient to these challenges, with potential applications in healthcare,...
This $163,265 award from the National Science Foundation's Mathematical and Physical Sciences (CFDA 47.049) program funds the development of a new algorithm to efficiently explore uncertainties in trillion-dimensional machine learning models. The University of Arizona will lead this "EAGER: SEARCH-ACCELERATED MARKOV CHAIN MONTE CARLO ALGORITHMS FOR BAYESIAN NEURAL NETWORKS AND TRILLION-DIMENSIONAL PROBLEMS" project, which aims to create a method that can explore high-dimensional parameter spaces over 500 times faster than existing approaches. The new algorithm could revolutionize machine learning across scientific and commercial fields by enabling the rigorous quantification of model uncertainties, which is critical for applications like astronomy, driverless cars, and medical diagnostics. The project will also involve work to support veterans transitioning from the military to college. The results will be released as open-source software and an open-access publication. No subawards are planned under this award, which runs from April 2024 through March 2025.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $163.3k | 3/26/24 |