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Ziwei Wang supervises 3 postgraduate research students. If these students have produced research profiles, these are listed below:

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Dr Ziwei Wang

Lecturer in Robotics

Ziwei Wang

D11, D - Floor

Engineering Building



Tel (mobile): +44 (0)7707 639777

Research overview

  • Physical human-robot interaction
  • Sensory and motor augmentation in teleoperation
  • Haptic communication between humans and robots 
  • Game theory-based interaction control
  • Data-driven neuromechanics modelling
  • Machine learning applications in robotics
  • Robotic rehabilitation and assessment

PhD supervision

If you are interested in doing a Ph.D. on human-robot interaction or teleoperation in extreme environments (details of research topics can be found on Research Interests) or postdoctoral Fellowships via external funding sources (e.g., Marie-Curie). Please send a copy of your CV and a summary of your research interests.


Ziwei Wang is a Lecturer in Robotics at Lancaster University and a member of the Lancaster Intelligent, Robotic and Autonomous Systems Centre (LIRA). He received the Ph.D. degree from the Department of Automation at Tsinghua University, China. Prior to joining Lancaster University, he worked as a Research Associate with the Human Robotics Group in the Department of Bioengineering at Imperial College London, U.K. He is also a Visiting Scholar at King’s College London, UK. His main research interests and expertise span a broad range of areas in teleoperation systems, human sensorimotor augmentation, and human-robot interaction, aiming at enhancing human sensorimotor capability and overall robotic system performance.

He is enthusiastic about developing AI-based telerobotics and control technologies to overcome the challenges in remote manipulation so that the benefits can be extended to remote surgery, space assembly and smart manufacturing. 1) Prescribed-Performance Teleoperation: A novel concept (termed as practically prescribed-time stability) and systematic approach for general teleoperation systems, which ensured user-defined characteristics of performance metrics such as operation time, accuracy, and state constraints. 2) Haptic Augmentation: He developed a Gaussian-process-based classifier for interactive environment identification and polynomial fuzzy based force estimation. These techniques have been successfully tested in the peg transfer task via Da Vinci surgical robot, which enables a robust estimation accuracy (<0.025N) with few-shot data through virtues of the fitting ability of polynomials and the nonlinear expression ability of fuzzy models. 3) Multiple Cooperative Teleoperation: He developed a series of reinforcement learning mechanisms to improve operation expertise and correct the operator commands before driving the remote devices, which allows for human-human and human-robot interaction in extreme environments.

He has authored and co-authored over 50 journals and conference papers, and some are published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Fuzzy Systems, IEEE Transactions on Industrial Informatics, etc.  He serves as an editorial board, a program committee member, and a reviewer for various international journals and international conferences. He was supported by the Co-Investigator of Future AI and Robotics for Space (FAIR-SPACE) Hub funded by EPSRC. He has also served as a Session Chair of IEEE SMC 21, ICAC 23 and IECON23, a Special Session Chair of IEEE WCCI 22, IECON 23, a Workshop Organiser of IROS 21, and a member of the technical program committee for a number of international conferences in the fields of AI and robotics. He has served as an Editorial Board Member of Frontiers in Robotics and AI and Designs. He is an IEEE Member and a CSF Member. He has served as a Technical Community Member of the IEEE Robotics and Automation Society (RAS) and IEEE Computational Intelligence Society (CIS), such as Collaborative Automation for Flexible Manufacturing, Human-Robot Interaction & Coordination, and Telerobotics. He was the recipient of the Young Author Award at the IFAC Workshop on Control Applications of Optimization in 2018, the Best Paper Award of the IEEE International Conference on Automation and Computing in 2022, and the Best Poster Award of IROS Workshop 2022. He served as the Academic Advisor for the First Prize of the 2021 International Collegiate Spacecraft Innovation Design Contest.

Current Teaching

ENGR216: Engineering Mechanics

ENGR415: Machine Learning in Engineering

ENGR204: Engineering Projects (Support)

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