Interests: Assured and Intelligent Cyber-Physical Robotic Systems.
Physical/Embodied 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
Affiliation: Lucy Institute, Robotics@ND
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.
Recent News (More)
[Oct. 2026] Invited Talk: I gave a talk on Assured and Intelligent Cyber-Physical Systems in Towards the Next Generation of CPS, a Workshop on the 20th Anniversary of the NSF CPS Program. Thanks NSF for the invitation.
[Oct. 2026] Invited Talk: I gave a talk on Assured and Intelligent Cyber-Physical Systems in Robotics Seminar Series at NC State University. Thanks Zhishan for the invitation.
[Oct. 2026] Benchmark: while VLA benchmarks usually ask whether a robot finishes the task, our SafeVLA-Bench also asks whether it did so safely! Check more on https://safevla.org!
[Sep. 2026] Paper: our paper "Exploiting Fine-Tuning Structures to Improve Adversarial Transferability on Downstream SAM", has been accepted by the Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS). Congratulations to Shixiong and all!
[April 2026] Paper: our paper "Deadline-Safe Control Synthesis for Cyber-Physical Systems with Reinforcement Learning", has been accepted by ACM Transactions on Embedded Computing Systems (TECS), 2026.
[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!