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.

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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.

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.

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

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