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Kelly Zhu

MSc in Computer Science
University of Toronto
zhu (at) cs.toronto.edu


About Me

I’m a second-year Computer Science MSc student at the University of Toronto, supervised by David Lindell and Kyros Kutulakos in the Toronto Computational Imaging Group. Previously, I received my BASc in Engineering Science at the University of Toronto, where I was fortunate to be advised by Florian Shkurti.

My MSc research is gratefully supported by the Vector Scholarship in AI, Queen Elizabeth II Graduate Scholarship in Science & Technology, and Ontario Graduate Scholarship.

Research

I am broadly interested in computational imaging, computer vision, machine learning, and robotics.

News

Publications

  1. ACM TOG
    Generating the Past, Present and Future from a Motion-Blurred Image
    SaiKiran Tedla, Kelly Zhu, Trevor Canham, Felix Taubner, Michael S. Brown, Kiriakos N. Kutulakos, David B. Lindell
    ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2025)
    PDF Project Page BibTex

  2. ICCV
    MV-DeepSDF: Implicit Modeling with Multi-Sweep Point Clouds for 3D Vehicle Reconstruction in Autonomous Driving
    Yibo Liu, Kelly Zhu, Guile Wu, Yuan Ren, Bingbing Liu, Yang Liu, Jinjun Shan
    International Conference on Computer Vision (ICCV 2023)
    PDF BibTex

Research Experience

  1. Undergraduate Thesis Student (Supervised by Prof. Florian Shkurti)
    RVL Lab
    Sep 2023 - Sep 2024 | University of Toronto

    Contributed to a multi-agent 3D detection and trajectory prediction model from multi-sweep LiDAR data to achieve real-time, collision-free motion planning


  2. DAAD RISE Intern (Supervised by Prof. Alexander Braun)
    safe.trAIn by Siemens AG
    May 2023 - Aug 2023 | Hochschule Düsseldorf

    Built a 3D point cloud landmark extraction pipeline using LiDAR and camera data for refinement of camera calibration techniques in autonomous train technology


  3. Perception Researcher
    Huawei Noah's Ark Lab
    May 2022 - Apr 2023 | Toronto, ON

    Developed perception and simulation systems for autonomous vehicles. Topics of research included 3D reconstruction, LiDAR sensor simulation, object detection, and multimodal scene understanding.


  4. Undergraduate Researcher (Supervised by Prof. Jonathan Kelly)
    STARS Lab
    May 2021 - Sep 2021 | University of Toronto

    Investigated efficient path planning on weighted graph maps for planetary navigation, using NASA’s Mars 2020 Rover Mission as a performance benchmark


  5. Undergraduate Researcher (Supervised by Prof. Andrew Goldenberg)
    Robotics and Automation Lab (RAL)
    May 2020 - Aug 2020 | University of Toronto

    Designed and prototyped an autonomous bed-making robot on a 6-DoF robot arm mounted on a mobile platform. Responsible for depth camera calibration and LiDAR-based platform navigation.

Industry Experience

  1. Autonomy Engineering Intern
    Trimble Applanix
    May 2021 - Sep 2021 | Toronto, ON

    Aided with the development of LiDAR-based SLAM and perception solutions for integration with Applanix's inertial navigation system in autonomous driving applications

Teaching