Project Grant 2538975
- Federal Grant Award Summary The University of Texas at Arlington received a $364,952 Project Grant award from the National Science Foundation's Division of Computer and Network Systems under the Computer and Information Science and Engineering (CISE) program (CFDA 47.070) on July 15, 2025, with a completion date of June 30, 2030. This CAREER award supports research to secure connected autonomous vehicle stacks against adversarial input by developing methods that protect both high-level...
- Federal Grant Award Summary The National Science Foundation's Division of Computer and Network Systems awarded the University of Texas at Dallas a $309,669 CAREER grant effective August 1, 2025, through July 31, 2030, under the Computer and Information Science and Engineering program (CFDA 47.070). This project grant supports research into improving the attack resilience of robotic systems through a comprehensive cross-domain security framework that addresses vulnerabilities spanning both...
- Federal Project Grant Award Summary The National Science Foundation (NSF), Division of Computer and Network Systems, awarded $600,000 under the Computer and Information Science and Engineering program (CFDA 47.070) to the University of Colorado to develop advanced mathematical and computational tools for reachability analysis of nonlinear cyber-physical systems. The three-year project, initiated June 1, 2026, and concluding May 31, 2029, addresses a critical gap in safety verification for...
- This $272,238 Project Grant, awarded on July 15, 2024 by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports research to enhance the safety and reliability of autonomous vehicles. The project aims to identify vulnerabilities in the software and machine learning components of autonomous vehicle systems, and develop mitigation techniques to improve their overall resilience. The research will combine model-based and...
- Federal Grant Award Summary The National Science Foundation (NSF) Directorate for Engineering awarded the University of Texas at Arlington $299,963 on July 15, 2026, through its Engineering program (CFDA 47.041) to support collaborative research on scaling robust multi-agent systems. The project, which runs through June 30, 2029, will develop efficient learning methods and decentralized algorithms that enable autonomous multi-agent systems to perform reliably in real-world environments. The...
- Federal Project Grant Award Summary The National Science Foundation's Division of Information and Intelligent Systems awarded a $399,756 Project Grant to the University of Florida's Division of Sponsored Research, effective October 1, 2025 through July 31, 2027, under the Computer and Information Science and Engineering program (CFDA 47.070). This collaborative research initiative develops foundational qualitative and quantitative safety assessment methodologies for learning-enabled autonomous...
- Federal Grant Award Summary The National Science Foundation's Division of Computing and Communication Foundations awarded the University of New Mexico $105,454 under the Computer and Information Science and Engineering program (CFDA 47.070) on December 1, 2025, for a project titled "Scalable Formal Verification of ANN Controlled Cyber-Physical Systems." This Small grant supports the development of novel algorithms and software tools designed to formally verify artificial neural...
- This $1,499,949 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 enhance the safety of autonomous vehicle (AV) systems. The key focus areas include: Developing rational machine learning (ML) models that can accurately predict driving decisions based on valid rationales, rather than inappropriate extrapolations from common scenarios. Integrating hardware reliability into the...
- This $875,000 Project Grant, awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070), supports the development of "Performance Verification", an automated reasoning framework to evaluate the reliability and availability of complex networked systems. The project aims to create formal modeling and specification methods to represent the behavior of modern networked systems, along with automated techniques to generate...
- Federal Grant Award Summary The National Science Foundation (NSF), Division of Computer and Network Systems, awarded $659,317 to the University of Florida (Award Date: June 1, 2026; Completion Date: May 31, 2031) under the Computer and Information Science and Engineering program (CFDA 47.070) to develop assured reinforcement learning methods for cyber-physical systems. The project will deliver foundational research and open-source algorithmic tools enabling autonomous systems—such as...
The National Science Foundation's Division of Computer and Network Systems awarded a $597,192 Project Grant to the University of Texas at Dallas on July 15, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070). This research initiative, entitled "Zonotopes for Autonomy: Set-Based Methods for Verification and Falsification of Autonomous Vehicle Software Stacks," will develop mathematical and computational methods to verify and validate the safety and performance of autonomous cyber-physical systems (CPS) through June 30, 2029. The grant funds the development of set-based verification and falsification methodologies that employ hybrid zonotope representations—an efficient mathematical framework for representing unions of convex polytopes. These tools will enable researchers to analyze integrated autonomous vehicle software stacks composed of mapping, perception, planning, and control modules operating in closed-loop with physical systems. By providing a common mathematical language across heterogeneous layers of autonomy software that process diverse sensor inputs (cameras, radar, LiDAR), the research aims to establish a unified approach for bounding worst-case system behavior, thereby supporting safer and more verifiable deployment of autonomous systems in critical applications including self-driving vehicles, agricultural robotics, and unmanned aerial systems.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $597.2k | 7/2/26 |