My Experience

  • 3D object detection, tracking, and segmentation on point cloud data.
  • Model optimization and acceleration for efficient deployment on edge GPUs.
  • Building end-to-end products, e.g., YourArXiv — a personalized arXiv recommender using embedding-based retrieval (React + Flask + AWS).

Experience

 
 
 
 
 
NIO
Perception Team
NIO
February 2022 – December 2023 Beijing, China
  • Participated in the development of a human-in-the-loop auto labeling system for 4D (LiDAR + Camera) data.
  • Main contributor to a visualization and debugging tool for LiDAR and camera perception systems, adopted by engineers across multiple teams and featured in the company’s recruiting video.
  • Developed a web-based annotation tool, enabling human annotators to collect hundreds of hours of high-quality ground truth data for pedestrian movements in dense urban areas.
  • Trained and deployed a sequence-to-sequence time series model for pedestrian tracking using point cloud, utilizing the collected high-quality data; this model now serves as an API for the annotation tool to provide real-time tracking results.
 
 
 
 
 
University of Toronto
MS, Electrical and Computer Engineering
University of Toronto
August 2022 – August 2023 Toronto, Canada
  • GPA: 4.0/4.0.
  • Coursework: Neural Networks and Deep Learning, Introduction to Cloud Computing, Perception for Robotics, Cloud-Based Data Analytics
  • Took a leave of absence due to extended study permit processing time.