Project Grant 2551283
- The National Science Foundation Division of Computer and Network Systems awarded Georgia TECH Research Corp $360,000 on August 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a control-theoretic framework for reliable and robust deep neural networks with application to space cyber-physical systems. The project formulates deep neural network training as a feedback control design problem, leveraging optimal and robust control theory...
- The National Science Foundation Division of Computer and Network Systems awarded The Leland Stanford Junior University $320,000 on August 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a control-theoretic framework for certifying deep neural networks deployed on spacecraft. The project addresses the challenge of certifying learning-enabled components operating continuously aboard spacecraft by formulating deep neural network training as a...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of New Mexico $105,454 on December 1, 2025, to develop scalable formal verification algorithms and software tools for artificial neural network-controlled cyber-physical systems under the Computer and Information Science and Engineering program (CFDA 47.070). The project addresses the challenge of rigorously verifying the safety and reliability of autonomous systems—including autonomous...
- The National Science Foundation (NSF) awarded a $240,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of Central Florida (UCF) Board of Trustees Office of Research. The grant supports a 3-year research project to develop a theoretical analysis that sheds light on the robustness of neural network-based methods and the properties of adversarial training. The research aims to contribute to the development of more robust neural network-based...
- The National Science Foundation awarded a $472,060 project grant under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of North Texas for the period of May 15, 2023 to April 30, 2026. The grant supports the development of an enhanced open networked airborne computing platform to facilitate design, implementation, and testing of integrated control, computing, communication, and networking capabilities for airborne applications. Key deliverables include...
- The National Science Foundation Division of Computer and Network Systems awarded New York University $600,000 on March 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) for a U.S.–Ireland research and development partnership developing integrated modeling, analysis, and control frameworks to enhance resilience and safety in industrial control systems under cyber and physical threats. The project, performed in New York, New York, addresses how attacks...
- The National Science Foundation Division of Computer and Network Systems awarded Trustees of Dartmouth College $498,819 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop theoretically grounded, computationally efficient methods for safe multi-task learning and control on resource-constrained autonomous systems. The project integrates meta-learning, adaptive control, model predictive control (MPC), and embedded optimization to enable...
- 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,...
- The National Science Foundation Division of Computer and Network Systems awarded Columbia University $515,235 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop theoretically grounded methods for safe multi-task learning and control on resource-constrained autonomous systems. The project develops a computationally efficient framework integrating meta-learning, adaptive control, model predictive control, and embedded optimization to...
- This $298,450 National Science Foundation project grant supports research to quantify the error landscape of deep neural networks. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), the awardee New York University will employ statistical mechanics methods to characterize the basins of attraction in high-dimensional parameter spaces of deep learning models. The university will measure basin volume distributions and flatness as a function of network parameters...
The National Science Foundation Division of Computer and Network Systems awarded the University of New Mexico $320,000 on August 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a control-theoretic framework for reliable and robust deep neural networks with application to space cyber-physical systems. The project formulates deep neural network training as a distributional control problem, leveraging optimal and robust control theory techniques to address major challenges including uncertainty, noise, stability, expressiveness, and robustness in learning-enabled components aboard spacecraft. The research promotes integration of deep neural networks on board spacecraft to achieve trusted space autonomy for future space missions, conducted in close collaboration with the Space Vehicles Directorate of the Air Force Research Lab. The work delivers theoretical advances in constraint satisfaction and efficient DNN training with guarantees, as well as training for graduate and undergraduate students and dissemination through journal and conference publications, workshops, and seminar presentations. Performance occurs in Albuquerque, New Mexico, with a period of performance through July 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $320.0k | 8/11/26 |