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Professor Zhi-Qiang Zhang

Professor Zhi-Qiang Zhang

  • Position:
  • Areas of expertise: Computional Modelling and Simulation, Digtial Twins, Machine Learning; Deep Learning; Wearable Sensing and Robotics; Biomechanics; Musculoskeletal Modelling; Assistive Technology and Rehabilitation
  • Location: 1.69 School of Electronic & Electrical Eng
  • Website: LinkedIn | Googlescholar

Profile

Professor Zhang's research lies at the intersection of artificial intelligence, robotics, and biomedical engineering. After earning his Ph.D. in Electrical Engineering from the University of Chinese Academy of Sciences in 2010, he joined Imperial College London as a research associate, where he worked for five and a half years before moving to the University of Leeds in 2016.

His work aims to bridge the gap between engineering and medicine, advancing innovative solutions in digital healthcare and personalized medicine. His research interests encompass neurorehabilitation, rehabilitation robotics, human biomechanics, computational modeling and simulation, AI, and wearable sensing technologies, with a strong focus on transformative technologies that improve human health and rehabilitation outcomes.

 

Research interests

Computer Simulation, Machine Learning/Artificial Intelligence, Computational In-silico Modelling

Neurorehabilitation, Neuromuscular Modelling, Human Biomechanics, Rehabilitation Robotics

Wearable Sensing and Robotic, Soft Robotics, Digital Medicine

Brain-Computer Interface, Physiological Signal Processing

<h4>Research projects</h4> <p>Any research projects I'm currently working on will be listed below. Our list of all <a href="https://eps.leeds.ac.uk/dir/research-projects">research projects</a> allows you to view and search the full list of projects in the faculty.</p>

Research groups and institutes

  • Institute of Design, Robotics and Manufacturing
  • Institute of Robotics, Autonomous Systems and Sensing
  • Assistive and rehabilitation robotics

Current postgraduate researchers

<h4>Postgraduate research opportunities</h4> <p>We welcome enquiries from motivated and qualified applicants from all around the world who are interested in PhD study. Our <a href="https://phd.leeds.ac.uk">research opportunities</a> allow you to search for projects and scholarships.</p>
Projects
    <li><a href="//phd.leeds.ac.uk/project/1267-computational-neuromusculoskeletal-modelling">Computational Neuromusculoskeletal Modelling</a></li> <li><a href="//phd.leeds.ac.uk/project/1273-contactless-sensing-for-vital-sign-monitoring">Contactless Sensing for Vital Sign Monitoring</a></li> <li><a href="//phd.leeds.ac.uk/project/1271-data-analytics-for-steady-state-visual-evoked-potential-based-brain-computer-interface">Data Analytics for Steady-State Visual Evoked Potential-based Brain-Computer Interface</a></li> <li><a href="//phd.leeds.ac.uk/project/1272-machine-learning-and-deep-learning-for-myoelectric-control">Machine Learning and Deep Learning for Myoelectric Control</a></li> <li><a href="//phd.leeds.ac.uk/project/1269-soft-sensing-and-actuation-for-upper-limb-rehabilitation">Soft Sensing and Actuation for Upper Limb Rehabilitation</a></li> <li><a href="//phd.leeds.ac.uk/project/1270-wearable-data-analytics">Wearable Data Analytics</a></li> <li><a href="//phd.leeds.ac.uk/project/1268-wearable-energy-harvester-from-human-gait">Wearable Energy Harvester from Human Gait</a></li> <li><a href="//phd.leeds.ac.uk/project/1050-wearable-sensing-for-stroke-rehabilitation">Wearable sensing for stroke rehabilitation</a></li>