Abstract
Cyber-physical systems (CPS) tightly couple computing and network components with physical processes via sensors and actuators. On the one hand, integration of AI enables autonomous CPS that perceive, understand, and perform complex tasks in the physical world. On the other hand, safety is critical for real-world CPS applications such as autonomous vehicles, drones, and various robotic systems. In this talk, Fanxin Kong will introduce his recent works on assured and intelligent CPS as follows: i) Foundation model-enabled CPS—this thread of works studies how to enhance safety of foundation models (e.g., large language models and vision-language action models) when applied to task/motion planning; ii) Secure and safe reinforcement learning (RL)—this thread of works addresses the synthesis of safe control policies using RL and explores safety-violation vulnerabilities of safe RL; and iii) Real-time attack-resilience for CPS—this thread of works discusses how to detect, diagnose, and recover from sensor faults/attacks in real-time and in a safe manner. System demonstrations with implementation of these works on multiple autonomous CPS simulators/testbeds will be also presented.
Speaker Biography
Fanxin Kong is an assistant professor in the Department of Computer Science and Engineering at the University of Notre Dame. His research centers around assured and intelligent cyber-physical systems with a focus on physical AI, safety and security, and real-time embedded systems, as well as their applications to various robotic systems. Kong has published over 85 research papers at top venues such as the Institute of Electrical and Electronics Engineers (IEEE) International Conference on Robotics and Automation, the ACM/IEEE International Conference on Cyber-Physical Systems, the IEEE Symposium on Real-Time Systems, the IEEE Real-Time and Embedded Technology and Applications Symposium, the IEEE/ACM International Conference on Embedded Software, and the Design Automation Conference; in various IEEE/ACM transactions; and books and book chapters. His research has been supported by the NSF, the Air Force Research Laboratory (AFRL), the Air Force Office of Scientific Research, and DARPA. He has received multiple awards such as the 2025 NSF CAREER Award, the 2025 ACM Special Interest Group on Embodied Systems (SIGBED) Early Career Researcher Award, and the AFRL Summer Faculty Extension Award in 2022 and 2024. Together with his students, Kong has won multiple competitions such as the 2024 Embedded System Software Competition at Embodied Systems Week and the 2024 ACM SIGBED Student Research Competition (SRC), as well as taking home the Best Scientific Research Award at the ACM SIGBED SRC in 2022.
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