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Chang Won (John) Lee

Hi there! I'm a Master's student at the University of Toronto, advised by Professor Steven Waslander in the Toronto Robotics and AI Lab. I am affiliated with University of Toronto Robotics Institute and Vector Institute. I obtained my Bachelor's degree in Engineering Science (Machine Intelligence major) from the University of Toronto.

My research lies at the intersection of machine learning, computer vision, and robotics. My previous and current work focuses on object detection, uncertainty quantification, multi-object tracking, and visual anomaly detection for autonomous driving and space robotics. Going forward, I am interested in exploring visual representation learning, generative modeling, multi-modal perception and 3D scene understanding.

CV     Github     G. Scholar     LinkedIn    

Please don't hesitate to reach out if you have any questions or would like to chat!

john [dot] lee [at] robotics [dot] utias [dot] utoronto [dot] ca

UofT

Master of Applied Science in Aerospace Engineering and Robotics
University of Toronto

September 2023 - September 2025 (Expected)
Advisor: Professor Steven Waslander

UofT

Bachelor of Applied Science in Engineering Science (Machine Intelligence)
University of Toronto

September 2018 - June 2023
Thesis Advisor: Professor Steven Waslander

FlowCLAS

FlowCLAS: Enhancing Normalizing Flow Via Contrastive Learning For Anomaly Segmentation

Chang Won Lee, Selina Leveugle, Svetlana Stolpner, Chris Langley, Paul Grouchy, Jonathan Kelly, Steven L. Waslander
Under Review
Paper

ALLO

ALLO: A Photorealistic Dataset and Data Generation Pipeline for Anomaly Detection During Robotic Proximity Operations in Lunar Orbit

Selina Leveugle, Chang Won Lee, Svetlana Stolpner, Chris Langley, Paul Grouchy, Steven Waslander, Jonathan Kelly
Under Review
Paper  •   Code

UncertaintyTrack

UncertaintyTrack: Exploiting Detection and Localization Uncertainty in Multi-Object Tracking

Chang Won Lee, Steven L. Waslander
2024 IEEE International Conference on Robotics and Automation (ICRA)
Paper  •   Code

ProPanDL

ProPanDL: A Modular Architecture for Uncertainty-Aware Panoptic Segmentation

Jacob Deery, Chang Won Lee, Steven Waslander
2023 20th Conference on Robots and Vision (CRV)
Paper

Presentation of UncertaintyTrack at ICRA 2024

2024

Teaching Assistant for Mathematics for Robotics (ROB310)

2023

Teaching Assistant for Mathematics for Robotics (ROB310)

2022

Teaching Assistant for Linear Algebra for Engineering (MAT188)
aUtoronto

Software Engineer (General Member) at aUToronto (August 2021 - April 2023)

University of Toronto's self-driving car team.
Our team won all dynamic and static challenges at the SAE AutoDrive Challenge II in 2024.

2019 - 2022

University of Toronto Engineering Student Ambassador

2020 - 2021

University of Toronto Engineering Student Mentor