Jiaying Fang

Jiaying Fang

Electrical Engineering Master Student

Stanford University


Jiaying Fang is an EE Master Student at Stanford University. She finished her BEng degree in Electronic and Information Engineering at HK PolyU. Her research interests include computer vision, deep learning, robotics perception, and autonomous vehicle. She was a member of the HK PolyU Autonomous Systems Lab and McGill DECAR Lab.

  • Computer Vision
  • Deep Learning
  • Robotics Perception
  • Autonomous Vehicle
  • MSc in Electrical Engineering, 2023 - 2025

    Stanford University

  • BEng in Electronic and Information Engineering, 2019-2023

    The Hong Kong Polytechnic University

  • Exchange Student, 2022

    McGill University


Deep Learning (PyTorch)
Computer Vision
Python / C++ / Java
Robot Operating System
Signal Processing


China Telecom AI
Machine Learning Engineer Intern
Jun 2023 – Aug 2022 Beijing
  • ICCV Challenge: As the main member of the team, participated in the ICCV'23 challenge: Open Fine Grained Activity Detection Challenge (OpenFAD). Currently, the team ranks at third place on the activity recognition track and second place on the activity detection track.
  • Foundation Model: Explored video foundation models like VideoMAE and UniFormer.
  • Model Inference Optimization: Made use of TensorRT to speed up a detection model based on YOLO.
DECAR Lab, McGill University Montreal, Canada
Research Assistant
May 2022 – Aug 2022 Montreal
  • Research: Researched estimation and control in the robotics field.
  • Controller Design: Designed and implemented a robust LQR controller which can be used in real-world applications.
  • Experiments: Conducted experiments about the LQR controller on an unmanned ground vehicle.
HK PolyU Autonomous Systems Lab
Research Assistant
May 2021 – Jun 2023 Hong Kong
  • Research about Visual Odometry: Researched visual odometry and simultaneous localization and mapping in the robotics field. Especially focusing on the integration of visual odometry and multi-object tracking.
  • Implementation of a Visual Odometry: Implemented a system with integration of deep learning-based visual odometry and multi-object tracking. Deep optical flow estimation and a 3D object detection network were used.


Outstanding Student Award - Faculty of Engineering
HKSAR Government Scholarship 2021/22 - HK$80,000
Wong Tit-shing Student Exchange Scholarship 2021/22 - HK$20,000
  • Best Academic Performance Award (2020/2021)
  • Best Academic Performance Award (2019/2020)
  • Best GPA Award (2020/2021)
  • Best GPA Award (2019/2020)
Professor Leung Tin-pui Memorial Scholarship 2020/21 - HK$20,000