Dr. Hongliang Lu is an Assistant Professor and PhD Supervisor in the Department of Mechanical and Energy Engineering at Southern University of Science and Technology. He received his B.Eng. degree in Vehicle Engineering from Dalian University of Technology in 2019, his M.Eng. degree in Mechanical Engineering from Beijing Institute of Technology in 2022, and his Ph.D. degree in Intelligent Transportation from The Hong Kong University of Science and Technology in 2025.

Dr. Lu’s research focuses on the closed-loop mechanisms of “perception–cognition–decision-making–action” in intelligent robots and autonomous systems. His main research interests include embodied manipulation, autonomous driving, brain-inspired intelligence, world models, and LLM agents. He is particularly interested in understanding how machines can comprehend the physical world, adapt to complex interactive environments, and develop intelligent behaviors with strong generalization and self-evolution capabilities.

In recent years, Dr. Lu has published more than 20 papers in leading international journals and conferences, including PNAS, Nature Reviews Electrical Engineering, Engineering, Transportation Research Part C, and IROS. His representative research has been featured in a special news report by The Hong Kong University of Science and Technology and has attracted broad attention in the fields of autonomous driving, embodied intelligence, and intelligent transportation.

In addition to academic research, Dr. Lu actively promotes industry–academia collaboration in embodied intelligence and intelligent robotic systems. In 2025, he served as a Senior Advisor at MoSense Technologies Co., Limited, focusing on embodied intelligence, tactile multimodal perception, and embodied manipulation, with the goal of advancing the real-world deployment of frontier intelligent technologies.

Education Experience：

2022.09–2025.10, Ph.D. in Intelligent Transportation, The Hong Kong University of Science and Technology
2019.09–2022.07, M.Eng. in Mechanical Engineering, Beijing Institute of Technology
2015.09–2019.07, B.Eng. in Vehicle Engineering, Dalian University of Technology

Professional Experience：
2026.07–Present, Assistant Professor, Department of Mechanical and Energy Engineering, Southern University of Science and Technology
2025.11–2026.06, Research Associate, The Hong Kong University of Science and Technology

Honors and Awards：
First Prize, Outstanding Ph.D. Graduate of the Department, November 2025

Representative Papers:

• H. Lu, M. Zhu, C. Lu, S. Feng, X. Wang, Y. Wang, and H. Yang. "Empowering Safer Socially Sensitive Autonomous Vehicles Using Human-plausible Cognitive Encoding." Proceedings of the National Academy of Sciences (PNAS), 122 (21) e2401626122, 2025.

• H. Lu, M. Zhu, and H. Yang. "Human-like driving technology for autonomous electric vehicles." Nature Reviews Electrical Engineering, 1-2, 2025.

• H. Lu, J. Yang, M. Zhu, C. Lu, X. Chen, X. Zheng, and H. Yang. "A knowledge-driven, generalizable decision-making framework for autonomous driving via cognitive representation alignment." Transportation Research Part C: Emerging Technologies, 172, 105030, 2025.

• H. Lu, C. Lu, H. Wang, J. Gong, M. Zhu, and H. Yang. "Scenario-level knowledge transfer for motion planning of autonomous driving via successor representation." Transportation Research Part C: Emerging Technologies, 169, 104899, 2024.

• H. Lu, J. Yang, Y. Liu, S. Shen, H. Liu, X. Zheng, and H. Yang. “Human-like Driving: A Comprehensive Survey from Depths and Breadths.” AI for Transportation, 2025.

• H. Lu, Y. Liu, M. Zhu, C. Lu, H. Yang, and Y. Wang, "Enhancing interpretability of autonomous driving via human-like cognitive maps: a case study on lane change." IEEE Transactions on Intelligent Vehicles, 9(9), 5739-5749, 2024.

• H. Lu, C. Lu, Y. Yu, G. Xiong, and J. Gong, "Autonomous overtaking for intelligent vehicles considering social preference based on hierarchical reinforcement learning." Automotive Innovation, 5, 195–208, 2022.

• C. Lu, H. Lu (Co-first), D. Chen, H. Wang, P. Li, and J. Gong, "Human-like decision making for lane change based on the cognitive map and hierarchical reinforcement learning." Transportation Research Part C: Emerging Technologies, 156, 104328, 2023.