Zhehua Zhou

Zhehua Zhou

Assistant Professor

About Me

I am currently an Assistant Professor in the Department of Electromechanical Engineering at University of Macau. My research interests include:

  • Learning-based control and optimal control
  • Dexterous manipulation, robot control, and motion planning
  • RL/ML in robotics, imitation learning, and transfer learning
  • Embodied AI for robotic systems
  • Safety analysis for AI-driven robotic system

I am focused on developing intelligent and robust AI-enabled autonomous and robotic systems with safety and reliability guarantees, ensuring their applicability to a wide range of complex real-world tasks and scenarios. Prior to joining the University of Macau, I was a Postdoctoral Research Fellow in the Department of Electrical and Computer Engineering at University of Alberta from 2022 to 2025, under the mentorship of Prof. Lei Ma and Prof. Zhan Shu. I received my Ph.D. from the Technical University of Munich in 2022, where I specialized in automatic control and robotics under the supervision of Prof. Martin Buss.

Available Positions:

Seeking exceptional Ph.D., Master’s, and Research Assistant (RA) candidates passionate about robotics research. We are looking for highly motivated students with strong academic backgrounds and a drive to tackle cutting-edge challenges in robotics. Competitive funding/support is available for outstanding applicants. Feel free to reach me at zhzhou@um.edu.mo!

News

  • 08/2025: I joined the Department of Electromechanical Engineering at University of Macau as an Assistant Professor.
  • 06/2025: Our paper “VLATest: Testing and Evaluating Vision-Language-Action Models for Robotic Manipulation” was presented at ACM FSE 2025!
  • 01/2025: Our paper “Multilingual Blending: LLM Safety Alignment Evaluation with Language Mixture” was accpeted by NAACL 2025!
  • 11/2024: Our paper “GenSafe: A Generalizable Safety Enhancer for Safe Reinforcement Learning Algorithms Based on Reduced Order Markov Decision Process Model” was published on IEEE Transactions on Neural Networks and Learning Systems!
  • 06/2024: We gave a tutorial on “Quality Assurance for Autonomous Driving Systems: A Software Engineering Perspective” at Autoware Tutorial, IEEE IV 2024.
  • 05/2024: Our paper “ISR-LLM: Iterative Self-Refined Large Language Model for Long-Horizon Sequential Task Planning” was presented at IEEE ICRA 2024!
  • 03/2024: Our paper “Towards Building AI-CPS with Nvidia Isaac Sim: An Industrial Benchmark and Case Study for Robotics Manipulation” was presented at IEEE/ACM ICSE-SEIP 2024!
  • 02/2024: Our paper “Enabling Versatility and Dexterity of the Dual-Arm Manipulators: A General Framework Toward Universal Cooperative Manipulation” was published on IEEE Transactions on Robotics!
  • 10/2022: Our paper “Off-Policy Risk-Sensitive Reinforcement Learning-Based Constrained Robust Optimal Control” was published on IEEE Transactions on Systems, Man, and Cybernetics: Systems!
  • 09/2022: I gave a talk on “Safe Reinforcement Learning with Model Order Reduction Techniques” at The 1st International Workshop on Safe Reinforcement Learning Theory and its Applications, IEEE MFI 2022.
  • 07/2022: I joined the Department of Electrical and Computer Engineering at University of Alberta as a Postdoctoral Research Fellow.
  • 07/2022: I received my Ph.D. degree from the Chair of Automatic Control Engineering (LSR) at the Technical University of Munich (TUM), supervised by Prof. Martin Buss.
  • 09/2021: Our paper “Learning a Low-Dimensional Representation of a Safe Region for Safe Reinforcement Learning on Dynamical Systems” was published on IEEE Transactions on Neural Networks and Learning Systems!
  • 06/2020: Our paper “A General Framework to Increase Safety of Learning Algorithms for Dynamical Systems Based on Region of Attraction Estimation” was published on IEEE Transactions on Robotics!

Featured Publications