MENS Lab

具身心智与进化智能实验室

Embodied Intelligence · World Models · Autonomous Driving · LLM Agents

MENS = Mind, Embodiment, NeuroAI, and Self-evolution

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About Us

MENS Lab is led by Hongliang Lu, an Assistant Professor (Associate Researcher) and Ph.D. Supervisor at the Southern University of Science and Technology (SUSTech). MENS stands for Mind, Embodiment, NeuroAI, and Self-evolution, reflecting our vision of intelligence as something that emerges through perception, physical interaction, memory, adaptation, and continuous growth.

The lab explores embodied intelligence, robotic manipulation, autonomous driving, world models, brain-inspired AI, and LLM agents, with the goal of building intelligent systems that do not merely compute, but sense the world, understand action, learn from experience, and evolve within complex real-world environments.

We warmly welcome motivated students and researchers to join us in exploring the future of embodied intelligence.

MENS Lab

Directions

Our research is organized around four core directions.

Embodied Manipulation

Embodied Manipulation

Building agents that perceive and act in the physical world, bridging sensing, manipulation, and reasoning.

World Model

World Model

Learning predictive models of the environment to enable planning, simulation, and robust sim-to-real transfer.

Autonomous Driving

Autonomous Driving

Perception, decision-making, and control for safe, adaptive self-driving systems in complex scenes.

LLM Agent

LLM Agent

Large language models as reasoning agents that plan, use tools, and interact with the physical world.

News

Content coming soon.

People

Supervisor
Hongliang Lu

Hongliang Lu 鲁洪良

Hongliang Lu is an Assistant Professor (Associate Researcher) and Ph.D. Supervisor in the Department of Mechanical and Energy Engineering at the Southern University of Science and Technology (SUSTech). He received his Ph.D. from the Hong Kong University of Science and Technology, with a research focus on embodied intelligence, autonomous driving, world models, brain-inspired AI, robotic manipulation, and LLM agents. His work explores how intelligent systems can perceive the physical world, reason about complex interactions, make adaptive decisions, and continuously evolve through experience.

As a first author, he has published in leading journals and conferences, including PNAS, Nature Reviews Electrical Engineering, Engineering, Transportation Research Part C, IEEE Transactions on Intelligent Vehicles, and other venues. His long-term research vision is to develop intelligent machines that can understand, act, and grow within real-world environments.

Contact: luhl3@sustech.edu.cn Google Scholar ↗

Ph.D. Students
Junjie Yang

Junjie Yang (co-supervised) 杨俊杰

Ph.D. student, The Hong Kong University of Science and Technology, Sep 2026 -
MPhil, The Hong Kong University of Science and Technology (Guangzhou), Sep 2024 - July 2026
B.Eng., University of Science and Technology Beijing, Sep 2020 - July 2024

Research: Autonomous Driving, Embodied Intelligence

Contact: jyang512@connect.hkust-gz.edu.cn

Ziyi Shi

Ziyi Shi (co-supervised) 施子逸

Ph.D. student, The Hong Kong University of Science and Technology, Sep 2025 -
MPhil, Zhejiang University, Sep 2022 - Jun 2025
B.Eng., Beijing Jiaotong University, Sep 2018 - Jun 2022

Research: AI Agents, RAG, LLM Memory

Contact: zshiay@connect.ust.hk

Master Students

Coming soon.

Research Assistants

Coming soon.

Alumni

Coming soon.

Selected Publications

2026

Human-inspired Data-light Cultural Alignment for Cross-regional Deployment of Autonomous Vehicles

H. Lu*, J. Yang, S. Shen, Z. Zang, Y. Li, J. Cao, C. Lu, X. Zheng, H. Yang

Nature Communications, Under Review

Reframing Urban Transportation As Complex Systems: A Three-Dimensional Evolutionary Perspective

H. Lu*, Z. Shi, H. Zhong, J. Yang, S. Shen, Y. Liang, X. Zheng, C. Lu, Q. Li, M. Xu, W. Liu, J. Ke, S. Feng, Z. Zhu, Y. Zheng, C. Xu, H. Yang

Engineering, Accepted in Principle

Coordinated Pandemic Control with Large Language Model Agents as Policymaking Assistants

Z. Shi, X. Guo, H. Lu*, M. Peng, H. Wang, Z. Zhu, Z. Li, Y. Liang, X. Zheng, H. Yang

iScience, Under Review Paper

UniT: Unified Geometry Learning with Group Autoregressive Transformer

H. Wang, Y. Huang, Z. Kuang, H. Lu, X. Zheng, M. Yang, G. Hua

IEEE TPAMI, Under Review Paper

Dual-chirality Flexagon Linkages with Infinite Eversion and Surface Reconfigurability

J. Lin, Z. Miao, H. Zhang, K. Dong, H. Lu, H. Feng, J. S. Dai

PNAS, Accepted Paper

Diffusion-based 4D Trajectory Prediction and Distributed Control for UAV Swarms

T. Li, H. Lu, H. Li, X. Zheng

IROS 2026, Accepted Paper

Partners

Content coming soon.

Opportunities

We are recruiting Master’s and Ph.D. students for the 2027 cohort. We welcome highly motivated applicants interested in embodied AI, robot learning, world models, and LLM agents. Applicants with relevant research experience will be given priority consideration.

We are also continuously recruiting Research Assistants. Outstanding Research Assistants may receive priority recommendation for future Ph.D. applications.

Join MENS Lab and work with us on meaningful, exciting, and impactful research.