Xiao Wang

Xiao Wang is a research assistant and PhD student in the Cyber-Physical Systems Group at the Technical University of Munich since 2019. She holds a Master of Science in Mechanical Engineering from the same university (2018) and a Bachelor of Engineering in Vehicle Engineering from Tongji University, China.

Her research focuses on Motion Planning for Autonomous Vehicles, Formal Methods, and Safe Reinforcement Learning. She has supervised multiple theses exploring topics like constrained RL, online verification, imitation learning, and safety falsification for autonomous systems. Her teaching roles include exercises and practical courses on Artificial Intelligence and Motion Planning for Autonomous Vehicles since 2018.

Her publications (2020–2023) span journals like Transactions on Machine Learning Research and conferences such as ITSC and FISITA, addressing challenges in safe RL, control barrier functions, and naturalistic traffic rule violations. She has also contributed to integrating the Apollo framework with the CommonRoad motion planning environment.

• Key research areas: Safe Reinforcement Learning, Motion Planning, Formal Verification, Autonomous Driving, Control Barrier Functions, Trajectory Prediction