Interests: Assured and Intelligent Cyber-Physical Robotic Systems.
Embodied/Physical AI: reinforcement learning, neuro-symbolic AI, and foundation models.
Security: attack detection, diagnosis, and recovery.
Safety: timing and functional correctness.
Applications: Robotic systems.
Email: fkong at nd dot edu
Other profiles: Google Scholar, dblp Entry
Short Bio
Dr. Fanxin Kong is a tenure-track assistant professor in the Department of Computer Science and Engineering at University of Notre Dame. Before that, he worked as a tenure-track assistant professor at Syracuse University and as a postdoctoral researcher with Prof. Insup Lee in the PRECISE Center at University of Pennsylvania. He obtained his Ph.D. in Computer Science at McGill University advised by Prof. Xue Liu.
I am looking for self-motivated PhD students. If you are interested in my research and working with me, please directly contact me with your CV.
Tools
SafePilot: Toolbox for Assuring LLM-Enabled Cyber-Physical Robotic Systems. [Link]
CPSim: Simulation and Security Toolbox for Cyber-Physical Systems. [Link]
Recent News (More)
[Mar. 2026] Award: Zifan has received the 2026 All University Doctoral Prize. Big congratulations to Zifan!
[Jan. 2026] Paper: our paper "SafeNet: A Neural-Symbolic Network for Safe Planning in Robotic Systems using Formal Method-Guided LLM Fine-Tuning", has been accepted for presentation at the 2026 IEEE International Conference on Robotics and Automation (ICRA). Congratulations to Zifan and Jialiang!
[Jan. 2026] Paper: our paper "Vulnerability Exploration of Safe Reinforcement Learning in Cyber-Physical Systems via STL Mining", has been accepted by the 17th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS) 2026, part of CPS-IoT Week 2026. Congratulations to Jialiang!
[Jan. 2026] Award: I hvae received the 2025 ACM SIGBED Early Career Researcher Award! Many thanks to ACM SIGBED! Many thanks to my nominator!
[Jan. 2026] Presentation: our abstract "LLM-Based Software Test Generation", has been accepted by the Flight Software Workshop (FSW) 2026. Congratulations to Weizhe!
[July 2025] Paper: our paper "Vulnerability Analysis for Safe Reinforcement Learning in Cyber-Physical Systems", has been accepted by Transactions on Cyber-Physical Systems. Congratulations to Shixiong!
[Apr. 2025] Award: I received the NSF CAREER Award on Security Foundations of Safe Learning Enabled Cyber-Physical Systems! Thanks NSF!
[Mar. 2025] Job: Mengyu will join Washington State University as an Assistant Professor in Fall 2025! Congratulations to Mengyu!
[Mar. 2025] Job: Zifan will join Meta as a Research Scientist. Congratulations to Zifan!
[Feb. 2025] Presentation: our abstract "LLM-enabled Software Testing", has been accepted by the High Confidence Software and Systems Conference (HCSS), 2025. Congratulations to Weizhe!
[Feb. 2025] Competition: Mengyu has been selected as a 2025 Cyber-Physical Systems (CPS) Rising Star. Congratulations to Mengyu!
[Feb. 2025] Paper: our work "Survey of signal temporal logic specification mining: techniques, applications, and future directions", has been accepted by the Defense + Commercial Sensing 2025. Congratulations to Jialiang!
[Feb. 2025] Paper: our paper "Query-Based Black-Box Stealthy Sensor Attacks on Cyber-Physical Systems", has been accepted by the 62nd the Chips to Systems Conference (DAC), 2025. Congratulations to Shixiong!
[Jan. 2025] Paper: our paper "Recovery-Guaranteed Sensor Attack Detection for Cyber-Physical Systems", has been accepted by the 31st IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), 2025, part of CPS-IoT Week 2025. Congratulations to Weizhe!
[Oct. 2024] Competition: Our SafePilot tool for assuring LLM-Enabled CPS has won the championship of Embedded System Software Competition (ESSC) at ESWEEK'2024! Big congratulations to Weizhe and Mengyu!
[Oct. 2024] Competition: My PhD student, Mengyu Liu, has won the championship of ACM SIGBED Student Research Competition (SRC) 2024! Big congratulations to Mengyu!
Recent Publications (Full Publications)
LLM/FM-Enabled Systems:
[ICRA'26] Zifan Wang, Jialiang Fan, Rui Zuo, Qinru Qiu, and Fanxin Kong, "SafeNet: A Neural-Symbolic Network for Safe Planning in Robotic Systems using Formal Method-Guided LLM Fine-Tuning", in the IEEE International Conference on Robotics and Automation, 2026.
[HCSS'25] Weizhe Xu and Fanxin Kong, "LLM-enabled Software Testing", in the 25th Annual High Confidence Software and Systems Conference, 2025.
[ICCPS'24] Weizhe Xu, Mengyu Liu, Steven Drager, Matthew Anderson, and Fanxin Kong, "Assuring LLM-Enabled Cyber-Physical Systems", in the 15th ACM/IEEE International Conference on Cyber-Physical Systems, Poster/Demo Track, part of CPS-IoT Week 2024.
[FMSys'24] Weizhe Xu, Mengyu Liu, Oleg Sokolsky, Insup Lee, and Fanxin Kong, "LLM-enabled Cyber-Physical Systems: Survey, Research Opportunities, and Challenges", International Workshop on Foundation Models for Cyber-Physical Systems & Internet of Things, co-located with CPS-IoT Week 2024.
Secure & Safe Reinforcement Learning:
[ICCPS'26] Jialiang Fan, Shixiong Jiang, Mengyu Liu, and Fanxin Kong, "Vulnerability Exploration of Safe Reinforcement Learning in Cyber-Physical Systems via STL Mining", in the 17th ACM/IEEE International Conference on Cyber-Physical Systems, 2026.
[EMSOFT'24] Shixiong Jiang, Mengyu Liu, and Fanxin Kong, "Backdoor Attacks on Safe Reinforcement Learning-Enabled Cyber-Physical Systems", in the ACM SIGBED International Conference on Embedded Software, part of Embedded Systems Week (ESWEEK) 2024.
[ICCPS'24] Shixiong Jiang, Mengyu Liu, and Fanxin Kong, "Vulnerability Analysis for Safe Reinforcement Learning in Cyber-Physical Systems", in the 15th ACM/IEEE International Conference on Cyber-Physical Systems, part of CPS-IoT Week 2024.
Timing-Safe Learning Enabled Systems:
[RTSS'24] Mengyu Liu, Pengyuan Lu, Xin Chen, Oleg Sokolsky, Insup Lee, and Fanxin Kong, "Deadline-Safe Reach-Avoid Control Synthesis for Cyber-Physical Systems with Reinforcement Learning", in the 45th IEEE Real-Time Systems Symposium, 2024.
[MEMCODE'24] Mengyu Liu, Pengyuan Lu, Xin Chen, Oleg Sokolsky, Insup Lee and Fanxin Kong, "Model-free PAC Time-Optimal Control Synthesis with Reinforcement Learning", in the 22nd International Symposium on Formal Methods and Models for System Design, colocate with Embedded Systems Week, 2024.
Attack Recovery:
[RTAS'24] Lin Zhang, Luis Burbano, Xin Chen, Alvaro A. Cardenas, Steve Drager, Matthew Adderson, and Fanxin Kong, "Fast Attack Recovery for Stochastic Cyber-Physical Systems", in the 30th IEEE Real-Time and Embedded Technology and Applications Symposium, 2024.
[RTSS'23] Mengyu Liu, Lin Zhang, Vir Phoha, and Fanxin Kong, "Learn-to-Respond: Sequence-Predictive Recovery from Sensor Attacks in Cyber-Physical Systems", in the 44th IEEE Real-Time Systems Symposium, 2023.
[RTAS'23] Lin Zhang, Kaustubh Sridhar, Mengyu Liu, Pengyuan Lu, Xin Chen, Fanxin Kong, Oleg Sokolsky and Insup Lee, "Real-Time Data-Predictive Attack-Recovery for Complex Cyber-Physical Systems", in the 29th IEEE Real-Time and Embedded Technology and Applications Symposium, 2023.
[EMSOFT'21] Lin Zhang, Pengyuan Lu, Fanxin Kong, Xin Chen, Oleg Sokolsky and Insup Lee, "Real-Time Attack-Recovery for Cyber-Physical Systems using Linear-Quadratic Regulator", in the 21st ACM SIGBED International Conference on Embedded Software, 2021.
[RTSS'20] Lin Zhang, Xin Chen, Fanxin Kong, and Alvaro A. Cardenas, "Real-Time Recovery for Cyber-Physical Systems using Linear Approximations", in the 41st IEEE Real-Time Systems Symposium, 2020.
[ICCPS'18] Fanxin Kong, Meng Xu, James Weimer, Oleg Sokolsky and Insup Lee, "Cyber-Physical System Checkpointing and Recovery", in the 9th ACM/IEEE International Conference on Cyber-Physical Systems, 2018.
Attack Detection & Diagnosis:
[RTAS'25] Weizhe Xu, Xin Chen, Matthew Anderson, Steven Drager, and Fanxin Kong, "Recovery-Guaranteed Sensor Attack Detection for Cyber-Physical Systems", in the 31st IEEE Real-Time and Embedded Technology and Applications Symposium, 2025.
[RTSS'23] Zifan Wang, Lin Zhang, Qinru Qiu, and Fanxin Kong, "Catch You If Pay Attention: Temporal Sensor Attack Diagnosis Using Attention Mechanisms for Cyber-Physical Systems", in the 44th IEEE Real-Time Systems Symposium, 2023.
[DAC'22] Lin Zhang, ZifanWang, Mengyu Liu, and Fanxin Kong, "Adaptive Window-Based Sensor Attack Detection for Cyber-Physical Systems", in the 59th Design Automation Conference, 2022.
[RTAS'21] Francis Akowuah and Fanxin Kong, "Real-Time Adaptive Sensor Attack Detection in Autonomous Cyber-Physical Systems", in the 27th IEEE Real-Time and Embedded Technology and Applications Symposium, 2021.
[DAC'20] Tianjia He, Lin Zhang, Fanxin Kong, and Asif Salekin, "Exploring Inherent Sensor Redundancy for Automotive Anomaly Detection", in the 57th Design Automation Conference, 2020.
Vunlnerability analysis for safe reinforcement learning
No recovery vs real-time attack recovery, indoor autonomous vehicles
Drone path recovery