Yinglong Miao

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I am a robotics researcher and engineer, and a computer science enthusiast. I have been working in robotics field since 2018, focusing on robotic manipulation with perception in the loop, task and motion planning, and learning-based motion planning. I have worked at PRACSYS lab advised by Dr. Kostas Bekris from 2020 to 2024, where I worked on robotic manipulation projects on a Motoman SDA10F robot. Prior to this, I have worked at ARCLab during my Master’s prgram at UCSD, where I had the opportunity to be advised by Dr. Michael Yip and Dr. Ahmed Qureshi, and worked on projects about learning-based motion planning. I participated on the project of MPNet. Before joining UCSD, I obtained BS in CS from the Chinese University of Hong Kong, where I had the pleasure to work with Dr. Leizhen Cai briefly on graph theory algorithms.

news

Nov 01, 2024 Finishing with M.Sc. in Computer Science at Rutgers in April or May 2025. Looking for jobs!
Aug 01, 2021 Finished Advanced Robotics Internship at Siemens. Our work is featured at the ARM Institute.
May 01, 2021 Joining for an Advanced Robotics Internship at Siemens.
Sep 01, 2020 Graduated with M.Sc. in Computer Science from UCSD. Joining PRACSYS Lab advised by Dr. Kostas Bekris for PhD in Computer Science at Rutgers.
Sep 01, 2018 Joining ARCLab at UCSD.
Jul 01, 2018 Graduated with B.Sc. in Computer Science from the Chinese University of Hong Kong. Joining for M.Sc. in Computer Science in UCSD.

selected publications

  1. isrr-2022-spotlight.gif
    Safe, occlusion-aware manipulation for online object reconstruction in confined spaces
    Yinglong Miao, Rui Wang, and Kostas Bekris
    In The International Symposium of Robotics Research, 2022
  2. ral-2021-mpc-mpnet.gif
    MPC-MPNet: Model-predictive motion planning networks for fast, near-optimal planning under kinodynamic constraints
    Linjun Li, Yinglong Miao, Ahmed H Qureshi, and 1 more author
    IEEE Robotics and Automation Letters, 2021
  3. mpnet-rigid-body.gif
    Motion planning networks: Bridging the gap between learning-based and classical motion planners
    Ahmed Hussain Qureshi, Yinglong Miao, Anthony Simeonov, and 1 more author
    IEEE Transactions on Robotics, 2020