Fangqiang Ding

PhD Candidate @ School of Informatics, University of Edinburgh

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Pentland Hills, 2023

about me

I am a third-year PhD student (since Fall 2021) from the MAPS Lab at the University of Edinburgh, sponsored by the EPSRC CDT in Robotics and Autonomous Systems, supervised by Dr. Chris Xiaoxuan Lu and Prof. Barbara Webb. My expertise lies in developing robust and privacy-aware spatial, semantic and motion perception systems for embodied AI, encompassing mobile robots, autonomous vehicles (AVs), extended reality (XR) and human-robot interaction (HRI) devices. At the core of my research is exploiting two types of sensors, the mmWave imaging radar and thermal camera, to cope with robustness challenges and privacy concerns found in perception for mobile autonomy and human behaviour recognition.

Before coming to Edinburgh, I received my B.Eng degree with the highest honour - Academic Star in 2020 from Tongji University (2017-2021).

👉 I am looking for self-motivated UG/Ms students to work with on cutting-edge research projects on AVs perception, multi-modal LLM and robot navigation. Support in the form of computational and sensory tools, alongside practical supervision and direction, is available.

👉 I am actively looking for a research intern position this year. Shoot me an email if you think I am a good fit!

news

Jan 29, 2024 🎉 One paper accepted to ICRA-2024. See you at Yokohama in May.
Jan 17, 2024 📖 One paper accepted to Engineering Applications of Artificial Intelligence (EAAI, Q1).
Sep 01, 2023 🎓 Successfully pass my 2nd-year PhD annual review and proceed to my 3rd PhD year.
Jun 01, 2023 🤖 Present my poster @ ICRA-2023 in London. See you next year.
Mar 01, 2023 🎉 Our paper Hidden Gems @ CVPR-2023 was selected as Highlight (top 10%).

selected publications

  1. ICRA’24
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    RaTrack: Moving Object Detection and Tracking with 4D Radar Point Cloud
    Fangqiang Ding, Zhijun Pan, Hantao Zhong, and 1 more author
    In IEEE International Conference on Robotics and Automation, 2024
  2. CVPR’23
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    Hidden Gems: 4D Radar Scene Flow Learning Using Cross-Modal Supervision
    Fangqiang Ding, Andras Palffy, Dariu M. Gavrila, and 1 more author
    In IEEE Conference on Computer Vision and Pattern Recognition, 2023
    Selected as Highlight (top 10%)
  3. RA-L/IROS
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    Self-Supervised Scene Flow Estimation with 4D Automotive Radar
    Fangqiang Ding, Zhijun Pan, Yimin Deng, and 2 more authors
    IEEE Robotics Autom. Lett. / IEEE International Conference on Intelligent Robots and Systems, 2022