Dr Fan Zhang was a Research Associate in the Personal Robotics Lab, Imperial College London, from Jan 2021 to Jan 2024. He received his Ph.D. degree also from Imperial College London (Personal Robotics Lab, advised by Prof. Yiannis Demiris) in Feb 2021, with the thesis topic: "Perception and Manipulation for Robot-Assisted Dressing".
His research interests cover many aspects of learning algorithms applied to assistive robotics and human-robot interaction. During his time with us, he worked on robot-assisted dressing for impaired patients. He also worked for the following projects: DRISK; Closed-Loop Multisensory Brain-Computer Interface for Enhanced Decision Accuracy; UKRI Trustworthy Autonomous Systems Node in Trust.
He has been awarded The Queen Mary UK Best PhD in Robotics Award 2020 1st place! More information about robot-assisted dressing can be found here. His research has been reported by Bloomberg, The Times. More information about Dr Fan Zhang can be found on his personal web page.
Publications
Journals
→ Zhang F, Demiris Y (2022). Learning garment manipulation policies toward robot-assisted dressing. Science Robotics, 7, eabm6010
→ Zhang F, Cully A, Demiris Y (2019). Probabilistic Real-Time User Posture Tracking for Personalized Robot-Assisted Dressing. IEEE Transactions on Robotics, 35.4: 873-888.
Conferences
→ Zhang F, Demiris Y (2020). Learning Grasping Points for Garment Manipulation in Robot-Assisted Dressing. International Conference on Robotics and Automation (ICRA 2020).
→ Zhang F, Cully A, Demiris Y (2017). Personalized Robot-Assisted Dressing using User Modeling in Latent Spaces. International Conference on Intelligent Robots and Systems (IROS 2017), pp: 3603-3610.
→ Zhang F, Yan Z, Du Z (2017). Preoperative Planning for the Multi-arm Surgical Robot using PSO-GP-based Performance Optimization. International Conference on Robotics and Automation (ICRA 2017), pp: 4208-4214.
→ Zhang F, Su Y, Zhang X, Dong W, Du Z (2015). An under-actuated manipulation controller based on Workspace Analysis and Gaussian Processes. International Conference on Intelligent Robots and Systems (IROS 2015), pp: 5629-5635.
