Yizhou (Philip) Huang

I am a first-year MSc student in Computer Science at the University of Toronto and a member of the Robot Vision and Learning (RVL) lab. I'm co-supervised by Prof. Florian Shkurti and Prof. Tim Barfoot. My research is generously funded by the CGS-M Scholarships and the Vector Scholarship in AI.

I have also been fortunate to work under many fantastic researchers in robotics. Previously, I collabrated with Prof. Fabio Ramos from Nvidia and on task and motion planning. In undergrad, I was involved in the student design team aUToronto, where we competed and won the SAE Autodrive Challenge. I also spent one amazing summer in Israel with Prof. Amir Degani and the summer before that with Prof. Angela Schoellig.

Email  /  CV  /  Google Scholar  /  LinkedIn  /  Twitter  /  Github

Research

The goal of my research is to improve robot's ability to model uncertain environments and make plans for complex and long-horizon tasks. Towards this end, I am currently working on planning algorithms for autonomous surface vessel (ASV) in Canadian lakes. Before that, I have also also explored continual learning in learning dynamics model for control.

Continual Model-Based Reinforcement Learning with Hypernetworks
Yizhou Huang, Kevin Xie, Homanga Bharadhwaj, Florian Shkurti
ICRA, 2021 and Deep RL Workshop (NeurIPS 20)  
project page / arXiv / video / code

Task-conditioned hypernetworks can be used to continually adapt to varying environment dynamics in lifelong model-based reinforcement learning, with a fixed-size replay buffer.

Zeus: A system description of the two-time winner of the collegiate SAE autodrive competition.
Keenan Burnett, Jingxing Qian, Xintong Du, Linqiao Liu, David J. Yoon, Tianchang Shen, Susan Sun, Sepehr Samavi, Michael J. Sorocky, Mollie Bianchi, Kaicheng Zhang, Arkady Arkhangorodsky, Quinlan Sykora, Shichen Lu, Yizhou Huang, Angela Schoellig, Timothy D. Barfoot,
Journal of Field Robotics, 2021  
arXiv / video

System design and development of the winning self-driving car in the AutoDrive Challenge, as well as lessons learned.

Misc
Reviewer, IROS 2022
Reviewer, MetaLearn Workshop NeurIPS 2020
Graduate Student Mentor, PRISM Workshop 2022
csc477 TA, CSC477 Fall 2021

This template is from Jon Barron's website. Here is the source code