PhD Success: Dr. Dianzhao Li Defends Thesis on Reinfocement Learning for Autonomous Driving

We are delighted to announce that Dianzhao Li from the Chair of Applied Statistics has successfully defended his PhD thesis, titled: "Deep Reinforcement Learning for Autonomous Driving: Human-Informed, Ethical, and Transferable Agents."

Dr. Li’s doctoral research, funded by ScaDS.AI, addresses critical challenges in the development of autonomous vehicle systems. His work bridges the gap between complex deep reinforcement learning architectures and the practical requirements for human-informed, ethical, and highly transferable decision-making agents.

The defense was overseen by a distinguished committee of experts in the field:

• Supervisors (Gutachter):

  • Prof. Dr. rer. pol. Ostap Okhrin, Chair of Applied Statistics, Faculty of Transportation and Traffic Sciences.

  • Prof. Dr. Liam Paull, Université de Montréal.

• Doctoral Committee:

  • Prof. Dr. Meng Wang, "Friedrich List" Faculty of Transportation and Traffic Sciences.

  • Prof. Dr.-Ing. Roberto Calandra, Faculty of Computer Science.

  • Dr. rer. nat. Martin Treiber, "Friedrich List" Faculty of Transportation and Traffic Sciences.

This achievement marks a significant contribution to the field of intelligent transportation systems and reinforces our commitment to advancing AI-driven mobility research. We congratulate Dr. Li on this milestone and look forward to his continued contributions to the scientific community.