About Me

My research focuses on autonomous driving systems, specifically learning-based planning, trajectory prediction, and decision-making under uncertainty. I work at the intersection of reinforcement learning, imitation learning, and classical motion planning to build robust autonomy stacks for multi-agent traffic environments. A key part of my work is designing scalable simulation-driven evaluation pipelines and developing safety-aware learning methods for autonomous driving systems.

My goal is to bridge research and production autonomy systems, enabling learning-based agents that are reliable, interpretable, and deployable in real-world driving scenarios.

News

• 2025.12 : An interview with me was published in NASW (National Association of Science Writers), where I discussed about how small robot vehicles can drive research and education innovation. The article is available here: NASW Interview.
• 2025.11 : I gave a talk at Safe Autonomy Seminar hosted by xLAB at the University of Pennsylvania, lead by Prof. Rahul Mangharam. The recording of the talk is available here: video link.
• 2025.08 : Our paper on ethical and responsible autonomous driving agents is now online.
• 2025.06 : Our survey paper focus on autonomous driving research for small-scale cars have been accepted for publication by IEEE TITS.
• 2024.10 : Our research was featured by Duckietown news .
• 2024.10 : Our paper with platform-agnostic DRL framework for Sim2Real transfer have been accepted for publication by Communications Engineering.
• 2023.09 : Our paper focus on vision-based DRL car following with Sim2Real transfer have been accepted for IEEE ITSC.
• 2023.04 : I am offcialy a doctoral candidate in TU Dresden.
• 2023.02 : Our paper Modified DDPG car-following model with a real-world human driving experience with CARLA simulator have been accepted for publication by TRC.
• 2022.10 : I attend the 27th Young Scientists Workshop in Statistical Week 2022.
• 2022.09 : We successfully hosted the Conference on Reinforcement Learning 2022 Dresden. A big thank you to all who attended and contributed to making it a success!

📝 Publications

MTA-RL: Robust Urban Driving via Multi-modal Transformer-based 3D Affordances and Reinforcement Learning
Guangli Chen ^†, Dianzhao Li^†, Wenjian Zhong, Bangquan Xie and Ostap Okhrin († equal contribution)

arXivUnder Review

Under review (IROS), 2026.

Paper

Learning to Drive Ethically: Embedding Moral Reasoning into Autonomous Driving
Dianzhao Li*, Ostap Okhrin

arXivUnder Review

Under review (IEEE TPAMI), 2025.

Paper Code

Autonomous Driving Small-Scale Cars: A Survey of Recent Development
Dianzhao Li*, Paul Auerbach, Ostap Okhrin

IEEE TITSPublished

IEEE Transactions on Intelligent Transportation Systems (IEEE TITS), 2025.

Paper Project

A platform-agnostic deep reinforcement learning framework for effective sim2real transfer towards autonomous driving
Dianzhao Li*, Ostap Okhrin

Nature Comms EngPublished

Communications Engineering, 2024.

Paper Project Code

Vision-based DRL Autonomous Driving Agent with Sim2Real Transfer
Dianzhao Li*, Ostap Okhrin

IEEE ITSCPublished

IEEE ITSC, 2023.

Paper Code

Modified DDPG car-following model with a real-world human driving experience with CARLA simulator
Dianzhao Li*, Ostap Okhrin

Transp. Res. Part CPublished

Transportation Research Part C: Emerging Technologies, 2023.

Paper Code

💼 Research Experience

2021.05 – Present

Research Scientist · Autonomous Driving & Reinforcement Learning

ScaDS.AI Dresden/Leipzig, Germany

Developed and evaluated reinforcement learning algorithms for autonomous driving, advancing robust policy transfer, cross-framework benchmarking, and simulation-to-real adaptability in high-fidelity environments.

2026.06 – Present

Visiting Researcher · Human-Guided Reinforcement Learning

University of Alberta, Canada

Research collaboration on preference-based reinforcement learning and human-guided decision-making for autonomous driving systems.

2024.10 – 2025.12

Research Associate · Intelligent Aircraft Cabin

GWT-TUD GmbH, Germany

Developed sensor-driven monitoring and inference pipelines using UWB radar and infrared sensing for intelligent cabin state analysis.

2019.06 – 2019.12

Research Intern · Machine Learning for Industrial Systems

Precitec GmbH & Co. KG, Germany

Developed an end-to-end machine learning toolchain with visualization tools, applied to quality monitoring in laser material processing using self-learning vision and multi-sensor systems, including feature engineering and data augmentation.

📖 Educations

2023.05 – 2026.05

PhD

Technische Universität Dresden

Advisor: Prof. Ostap Okhrin, Dr. Martin Treiber
Dissertation: Deep Reinforcement Learning for Autonomous Driving: Human-Informed, Ethical, and Transferable Agents

2017.03 – 2021.02

M.Sc. Mechanical Engineering (Mechatronics & Information Technology)

Karlsruher Institut für Technologie

Advisor: Prof. Marcus Geimer
Thesis: Where Am I? SLAM for Mobile Machines on a Smart Working Site

2012.09 – 2016.06

B.Sc. Mechanical Engineering and Automation (Control & Micro Control Technology)

China University of Petroleum (East China)

Advisor: Prof. Leilei Gao

📚 Referee for Journals and Conferences

• Since 2026, IEEE Transactions on Pattern Analysis and Machine Intelligence
• Since 2024, IEEE Transactions on Intelligent Transportation Systems
• Since 2024, SoftwareX
• Since 2024, Scientific Reports
• Since 2023, Engineering Applications of Artificial Intelligence
• Since 2022, Mathematical Biosciences and Engineering
• 2025 23rd European Control Conference (ECC)
• Transportation Research Board (TRB) Annual Meeting, Paper Reviewer for: AED30 Standing Committee on Information Systems and Technology and AED50 Standing Committee on Artificial Intelligence and Advanced Computing Application

💻 Teaching

• Theoretical Multivariate Statistics (Master)
• Applied Multivariate Statistics (Master)
• Data-Driven Multivariate Statistics (Master)

🛠️ Technical Skills