Jingyu Song

Jingyu Song | 宋靖宇 - PhD Candidate @ U-M Robotics

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Monterey Bay, CA, 2024.05

I am a third year PhD candidate at the University of Michigan Robotics Department, working with Prof. Katie Skinner at Field Robotics Group and Ford Center for Autonomous Vehicle. Before that, I graduated from the University of Michigan with an M.S. in Electrical and Computer Engineering in 2022, where I worked with Prof. Maani Ghaffari, and a B.E. in Electronics and Electrical Engineering from the University of Electronic Science and Technology of China and the University of Glasgow in 2020.

I was a research intern at NVIDIA in 2024, and a research intern at Bosch Corporate Research in 2020, an undergraduate research intern at Intel in 2018.

I am interested in the intersection of robotics, computer vision, and deep learning, with a focus on multi-modal perception, state estimation and mapping for 3D scene understanding. I am also interested in the application of these technologies in autonomous driving and field robotics.

news

Oct 28, 2024 Our paper MemFusionMap is accepted to WACV 2025! 🎉
Oct 14, 2024 We present our work 🐢 TURTLMap at IROS 2024! Check our LinkedIn Post!
Aug 23, 2024 I have concluded my internship at NVIDIA. It was a great experience working with the team pushing the boundaries of temporal reasoning for mapless autonomous driving 🚗. Check out our paper MemFusionMap on arXiv!

selected publications

  1. WACV
    MemFusionMap: Working Memory Fusion for Online Vectorized HD Map Construction
    Jingyu Song, Xudong Chen, Liupei Lu, Jie Li, and Katherine A Skinner
    arXiv preprint arXiv:2409.18737, 2024
  2. IROS
    TURTLMap: Real-time Localization and Dense Mapping of Low-texture Underwater Environments with a Low-cost Unmanned Underwater Vehicle
    Jingyu Song*, Onur Bagoren*, Razan Andigani, Advaith Venkatramanan Sethuraman, and Katherine A. Skinner
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
  3. CVPR
    CRKD: Enhanced Camera-Radar Object Detection with Cross-modality Knowledge Distillation
    Lingjun Zhao*Jingyu Song*, and Katherine A Skinner
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
  4. ICRA
    LiRaFusion: Deep Adaptive LiDAR-Radar Fusion for 3D Object Detection
    Jingyu Song, Lingjun Zhao, and Katherine A Skinner
    IEEE International Conference on Robotics and Automation (ICRA), 2024