Project Grant 2443803
Award Date
9/1/25
Completion Date
8/31/30
Dollars Obligated
$229K
Federal Agency
Division of Computer and Network Systems
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
Nashville, TN 37203, USA
Similar Awards
This Project Grant award, provided by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), supports research to characterize the vulnerabilities of learning-based controllers in networked cyber-physical systems (CPS). The $149,985 award will enable the University of Alabama in Huntsville (UAH) to develop real-time reward manipulation schemes, multi-level attack strategies, and data-enabled detection methods to...
This Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports research at Vanderbilt University focused on assuring the safety and efficacy of learning-enabled medical cyber-physical systems (LE-MCPS). The $255,978 award, spanning April 2024 to March 2029, aims to develop foundational techniques and tools for bridging the gap between experimentation and model-based design of LE-MCPS. The research...
This Project Grant award of $226,180, provided by the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070), supports research to enhance the security of cyber-physical systems (CPS) that utilize reinforcement learning, such as autonomous vehicles. The project will develop innovations to achieve safe and secure reinforcement learning, protecting users from system vulnerabilities and systems from attacks. Key focus areas...
This $300,027 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program supports research to develop secure and trustworthy learning-based control systems for cyber-physical systems (CPS). The project aims to: a) Develop a real-time reward manipulation scheme for learning-based controllers b) Design multi-level attack schemes on reward signals in a distributed CPS control architecture c) Develop data-enabled strategies for...
This Project Grant award, titled "CAREER: CERTIFIED EXPLANATIONS FOR TRUSTWORTHY ARTIFICIAL INTELLIGENCE", was provided by the National Science Foundation (NSF) through its Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070). The $119,764 award, granted on June 1, 2025, aims to develop a new paradigm of explainable AI systems with provable assurances to increase trust in high-stakes AI applications, such as in medical, scientific, and...
This $1,722,089 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CFDA 47.070) program aims to develop rigorous, scientific mechanisms to enable resilience in large-scale cyber-physical systems (CPS) against various perturbations. The award to Purdue University, effective June 15, 2024 through May 31, 2029, will focus on modeling and understanding the impacts of unintended errors, security attacks, unexpected interactions, and...
This $399,795 National Science Foundation project grant supports the development of an artificial intelligence and cyber-physical systems curriculum at Tennessee State University through July 2024. The grant aims to introduce underrepresented engineering students to the knowledge and opportunities needed for careers in high-demand AI-CPS fields. Specifically, the grant will fund the creation of a well-defined AI-CPS curriculum with cybersecurity, AI, and CPS components. This curriculum targets...
This Project Grant award from the National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $374,558 to the University of Florida to develop an approach for computing the predictive confidence in the safety of cyber-physical systems (CPS) powered by artificial intelligence (AI) that are experiencing anomalous behavior. The research aims to close the gap between anomaly detection and safety violations in AI-enabled CPS by designing...
The National Science Foundation (NSF) has awarded a $850,000 Project Grant under its Computer and Information Science and Engineering (CFDA 47.070) program to the University of California, Los Angeles (UCLA) to develop an efficient human-in-the-loop learning framework for human-centric cyber-physical systems (CPS). The 3-year project aims to create a novel approach to integrate human oversight and intervention into the training of CPS agents, such as assistive driving and exoskeleton systems, to...
This $200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) is for a 2-year planning project to develop a multi-university consortium focused on advancing the state of the art in applied cyber-physical systems (CPS) research. The key activities under this award include: Developing new monitoring and control paradigms for learning, estimation, and control of complex system-of-systems...