Hello! I am a Research Associate and Ph.D. candidate at the Professorship of Autonomous Vehicle Systems, School of Engineering and Design, Technical University of Munich, Germany, under the supervision of Professor Dr.-Ing. Johannes Betz. My research focuses on foundation-model-based scenario generation and analysis for autonomous driving. I have recently graduated with the double Master degree in Mechatronics and Robotics with high distinction, as well as Development, Production, and Management in Mechanical Engineering with distinction from the same university TUM in 2023.

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During my master's studies, I conducted my research at the Chair of Information-oriented Control under the supervision of Dr. Junjie Jiao and Professor Dr.-Ing. Sandra Hirche, where I completed my master's thesis. Prior to that, I worked as a student research assistant and wrote my term's thesis at the Chair of Automotive Technology under the supervision of Professor Dr.-Ing. Markus Lienkamp.

I earned my Bachelor's degree in Mechanical Design, Manufacture, and Automation with Excellent Graduate honors at School of Mechanical Engineering, Hefei University of Technology, China in 2017.

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Publications — Highlights

IROS'26 Chat2Scenic framework
Yuan Gao*, Wenting Miao, Mattia Piccinini, Haoyu Wang, Qunying Song, Johannes Betz
  • An iterative, RAG-based framework that turns natural-language descriptions into executable driving scenarios using retrieval-augmented LLMs.
ECCV'26 EgoDyn-Bench framework
Finn Rasmus Schäfer, Yuan Gao, Dingrui Wang, Thomas Stauner, Stephan Günnemann, Mattia Piccinini, Sebastian Schmidt, Johannes Betz
  • A benchmark for evaluating ego-motion understanding in vision-centric foundation models for autonomous driving.
ECCV'26 Target-Bench framework
Dingrui Wang, Zhihao Liang, …, Yuan Gao, …, Mattia Piccinini, Johannes Betz
  • A benchmark probing whether video world models can perform mapless path planning toward semantic targets.
OJ-ITS'26 Foundation models for autonomous driving — taxonomy
Yuan Gao*, Mattia Piccinini, Yuchen Zhang, Dingrui Wang, Korbinian Moller, …, Marco Pavone, Johannes Betz
  • A comprehensive survey of foundation models, LLMs, VLMs, MLLMs, Diffusion and world models, for scenario generation and scenario analysis in autonomous driving.
ICRA'26 NuRisk framework
Yuan Gao*, Mattia Piccinini, Roberto Brusnicki, Yuchen Zhang, Johannes Betz
  • A VQA dataset and benchmark for agent-level risk assessment in autonomous driving.
ITSC'25 From Words to Collisions
Yuan Gao*, Mattia Piccinini, Korbinian Moller, Amr Alanwar, Johannes Betz
  • LLM-guided evaluation and adversarial generation of safety-critical driving scenarios.
ACC'23
Yuan Gao*, Junjie Jiao, Sandra Hirche
  • Distributed control design for H2 suboptimal containment of multi-agent systems.
IFAC-WC'23
Yuan Gao*, Junjie Jiao, Sandra Hirche
  • H2 suboptimal leader–follower consensus control for multi-agent systems.

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