Fangyi Zhang

Research Fellow, QUT Centre for Robotics.


Since 2014, Dr. Fangyi Zhang has specialized in robotics and machine learning, establishing a robust record of publications and demonstrating leadership in both research and engagement. He has authored over 20 peer-reviewed publications, including contributions to top conferences and journals in robotics (IJRR, RA-L, ICRA, IROS) and machine learning (NeurIPS, ICLR). His academic excellence has been recognized with several awards, including a Best Paper Award Finalist at ACRA 2017 and a Best Industry Paper at IJCAIW 2021.

Dr. Fangyi Zhang is currently a research fellow in the QUT Centre for Robotics. He completed his PhD at the Australian Centre for Robotic Vision (ACRV) at QUT node, under the supervision of Prof. Peter Corke, Dr. Jürgen Leitner, and Prof. Michael Milford. His PhD research, which he completed in 2018, focused on Deep Reinforcement Learning and Transfer Learning for Robotic Reaching, and his thesis was titled “Learning Real-world Visuo-motor Policies from Simulation”. Following his PhD, he joined Alibaba DAMO Academy as an Algorithm Expert, where he worked on drone applications and data mining. His current research interests include robot learning, tactile sensing, robotic vision, robotic manipulation, and autonomous systems.

Before pursuing his PhD, Dr. Zhang earned his B.Eng. degree in Automation from East China Jiaotong University in 2010. He then spent three years working on R&D of locomotive control algorithms and electrical systems at the CRRC Zhuzhou Institute from 2010 to 2013. In 2014, he was a research assistant at the Hong Kong University of Science and Technology, supervised by Prof. Ming Liu, where he conducted research on VLC-based indoor localization and 2D-laser based 3D sensing.


Jul 17, 2024 Our RA-L paper “Towards assessing compliant robotic grasping from first-object perspective via instrumented objects” will be presented at the 40th Anniversary of the IEEE Conference on Robotics and Automation (“ICRA@40”).
May 17, 2024 Our 4th Workshop on Representing and Manipulating Deformable Objects will be held at ICRA 2024 on the 17th of May in PACIFICO Yokohama North Room: G304.
May 02, 2024 Our paper “Towards assessing compliant robotic grasping from first-object perspective via instrumented objects” got accepted to RA-L.
Oct 03, 2023 Our paper “Re-Evaluating Parallel Finger-Tip Tactile Sensing for Inferring Object Adjectives: An Empirical Study” was presented in IROS 2023.

selected publications

  1. Towards_Assessing.png
    Towards Assessing Compliant Robotic Grasping From First-Object Perspective via Instrumented Objects
    Maceon Knopke, Liguo Zhu, Peter Corke, and Fangyi Zhang
    IEEE Robotics and Automation Letters (RA-L), 2024
  2. re_evaluate_tactile.png
    Re-Evaluating Parallel Finger-Tip Tactile Sensing for Inferring Object Adjectives: An Empirical Study
    Fangyi Zhang, and Peter Corke
    In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2023
  3. Robust_Graph_Structure.png
    Robust Graph Structure Learning via Multiple Statistical Tests
    Yaohua Wang, Fangyi Zhang, Ming Lin, Senzhang Wang, Xiuyu Sun, and 1 more author
    In Advances in Neural Information Processing Systems (NeurIPS), 2022
  4. Face_Clustering_via.png
    Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
    Yaohua Wang, Yaobin Zhang, Fangyi Zhang, Senzhang Wang, Ming Lin, and 2 more authors
    In International Conference on Learning Representations (ICLR), 2022
  5. Adversarial_discriminative.png
    Adversarial discriminative sim-to-real transfer of visuo-motor policies
    Fangyi Zhang, Jürgen Leitner, Zongyuan Ge, Michael Milford, and Peter Corke
    The International Journal of Robotics Research (IJRR), 2019
  6. The_ACRV_picking.png
    The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research
    Jürgen Leitner, Adam W. Tow, Niko Sünderhauf, Jake E. Dean, Joseph W. Durham, and 13 more authors
    In IEEE International Conference on Robotics and Automation (ICRA), 2017