Shangding Gu

Shangding Gu is a Dr. rer. nat. (Doctor of Natural Sciences) working as a guest researcher at the Chair of Robotics, Artificial Intelligence and Real-time Systems at Technical University of Munich (TUM). He earned his Ph.D. in Computer Science from TUM in 2024 under the supervision of Prof. Alois Knoll. His research focuses on safe, robust, and reliable reinforcement learning systems with applications in foundation models, robotics, and semiconductor manufacturing.

• Workshop organizer: Trustworthy Interactive Decision-Making with Foundation Models at IJCAI 2024
• Founder of Safe Reinforcement Learning Online Seminar (2022-present)
• Current affiliations: TUM, Microsoft (internship 2023)

Research interests span Safe/Robust Reinforcement Learning, AI Safety, Motion Planning, and Autonomous Systems. His work has appeared in top venues like ICML, NeurIPS, and IEEE Transactions journals. He supervises students in robotics and AI topics including Multi-Agent RL, Trustworthy AI, and Multi-Robot Navigation.

Academic Service: Regular reviewer for 20+ conferences and journals including ICML, NeurIPS, ICLR, AAAI, ICRA, IROS, AAMAS, and IEEE Transactions series.