My name is Shangding Gu, now I am a postdoc in the Department of Electrical Engineering and Computer Sciences at UC Berkeley, USA, and a guest researcher at the Chair of Robotics and AI, TU Munich (TUM), Germany. I fortunately work with Prof. Costas Spanos and Prof. Ming Jin. I did a research internship at Microsoft from April 2023 to August 2023. In 2024, I earned my Ph.D. in Computer Science from TUM under the supervision of Prof. Alois Knoll.
406 Cory Hall, Berkeley, CA 94720
shangding.gu@berkeley.edu
Google Scholar
Personal Github
Safe RL Lab Github
Safe RL YouTube Channel
Research Interests
My current research focuses on reinforcement learning, planning, and AI safety, with applications in foundation models (e.g., large language models and multi-modal models), robotics, and semiconductor manufacturing. My goal is to design safe, reliable, and efficient systems that address pressing real-world challenges and drive impactful applications across diverse domains. My work has been featured in leading publications, including top-tier journals and conferences such as the Journal of Artificial Intelligence, IEEE Transactions on Pattern Analysis and Machine Intelligence, NeurIPS, and other prestigious venues. I support slow science. I am a student of mind, nature, and cosmos. If you are interested in my research topics, please feel free to contact me indicating your background and skills. Outside of research, I enjoy playing the guitar, reading, running, swimming and playing badminton with friends.
I am on the 2025-2026 job market looking for full-time academia and industry positions. Please feel free to reach out.Selected Recent Publications
Gu, S*., Shi, L*., Wen, M., Jin, M., Mazumdar, E., Chi, Y., Wierman, A., Spanos, C.
International Conference on Learning Representations, 2025.
Gu, S., Sel, B., Ding, Y., Wang, L., Lin, Q., Knoll, A., & Jin, M.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.
Gu, S., Knoll, A., & Jin, M.
Transactions on Machine Learning Research, 2024.
Gu, S*., Shi, L*., Ding, Y., Knoll, A., Spanos, C., Wierman, A., & Jin, M.
Advances in Neural Information Processing Systems, 2024.
Gu, S., Yang, L., Du, Y., Chen, G., Walter, F., Wang, J., & Knoll, A.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024.
Gu, S., Bilgehan S., Ding, Y., Wang, L., Lin, Q., Jin, M., Knoll, A.
Association for the Advancement of Artificial Intelligence, 2024.
Gu, S., Kuba, J. G., Chen, Y., Du, Y., Yang, L., Knoll, A., & Yang, Y.
The Journal of Artificial Intelligence, 2023.
Recent News
01.2025: Our paper on robust reinforcement learning got accepted by ICLR 2025
01.2025: We launched the 1st International Workshop on AI Agent Reasoning and Decision-Making (AIR 2025), see workshop homepage
01.2025: Received a grant from OpenAI's Researcher Access Program to support my research!
01.2025: Our paper on safe multi-objective reinforcement learning got accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence
12.2024: Our paper on reinforcement learning for data generation in large language models got accepted by Transactions on Machine Learning Research
12.2024: Invited as a member of the youth editorial board for the Journal of Artificial Intelligence and Autonomous Systems
12.2024: Our paper on mutual enhancement of reinforcement learning and large language models got accepted by AAAI 2025 Workshop LM4Plan
12.2024: Our paper on safe reinforcement learning for unmanned ship multi-objective path planning got accepted by Ocean Engineering
11.2024: Invited lecture on safe reinforcement learning and its applications in Virginia Tech's Machine Learning course
11.2024: Our paper on high-throughput parallel reinforcement learning framework got accepted by IEEE Transactions on Parallel and Distributed Systems
10.2024: Our paper on safe multi-agent reinforcement learning for autonomous driving got accepted by IEEE Transactions on Artificial Intelligence
09.2024: Our paper on efficient safe reinforcement learning got accepted by NeurIPS 2024
09.2024: We presented a tutorial on safe reinforcement learning for smart grid control and operations at IEEE SmartGridComm 2024, see Slides
09.2024: Our paper on safe reinforcement learning got accepted by IEEE Transactions on Pattern Analysis and Machine Intelligence (IF: 20.8)
08.2024: We presented a tutorial on safe reinforcement learning: bridging theory and practice at IJCAI 2024, see Slides
08.2024: Invited lecture on safe robot learning in WHUT summer course
07.2024: Our paper on robust safe robot learning got accepted by IEEE Transactions on Automation Science and Engineering (IF: 5.9)
05.2024: Join us at SmartGridComm 2024 Workshop on Safe RL for Smart Grid Control and Operations (Call for Contributions)
04.2024: Our paper on safe learning for real-world robot control got accepted by IEEE Transactions on Industrial Informatics (IF: 12.3)
03.2024: Join us at IJCAI 2024 Workshop on Trustworthy Interactive Decision Making with Foundation Models (Call for Contributions)
12.2023: Our paper on safety and reward balance for safe RL got accepted by AAAI 2024 (Oral Paper)
10.2023: Our paper on a safe human-robot learning framework got accepted by Frontiers in Neurorobotics
08.2023: Our paper on RL for autonomous driving parking lots got accepted by IEEE Transactions on Cybernetics (IF: 11.8)
06.2023: Our paper on offline RL with uncertain action constraint got accepted by IEEE Transactions on Cognitive and Developmental Systems
03.2023: Our paper on safe multi-robot learning got accepted by the journal of Artificial Intelligence (IF: 14.4)
12.2022: We launched a long-term safe reinforcement learning online seminar. Every month, we will invite at least one speaker to share cutting-edge research with RL researchers and students (each speaker has about 1 hour to share his/her research). We believe that holding this seminar can promote the research of safe reinforcement learning. For details, please see the Seminar Homepage
11.2022: Invited a safe RL talk at the RL China community
10.2022: Invited a safe RL talk at Prof. Jan Peters' lab
09.2022: We launched the 1st Safe RL Workshop @ IEEE MFI 2022