Shangding Gu, M.Sc.

E-Mail	shangding.gu(at)tum.de
Address	Boltzmannstr. 3 85748 Garching b. München Gemany
Office hours	appointment by email

Curriculum Vitae

I am a guest researcher at the Chair of Robotics, Artificial Intelligence and Real-time Systems. My research currently focuses on developing artificial intelligence methods and models, with a special interest in exploring the theory of safe reinforcement learning and motion planning, and its application in robotics, in which the goal is to enable robots to know how to learn, reason and plan, and enable robots to work in support of people.

See Personal Homepage

See Google Scholar

See Personal Github / SafeRL-Lab Github

Research Interests

Safe/Robust Reinforcement Learning; Reinforcement Learning Theory; AI Safety.
Motion Planning; Autonomous Driving; Robotics (e.g., arm robotics and marine robotics).

Safe Reinforcement Learning Workshop

We organized a safe reinforcement learning workshop, the researchers and students who are interested in safe RL are welcome to join us! The recorded videos are available on YouTube's Safe RL Channel, please see the YouTube Channel or Workshop Homepage.

Safe Reinforcement Learning Online Seminar

In December 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.