I received my BASc degree from Engineering Science (Robotics), UofT. Before joining DSL, I interned in Apple Siri team in Seattle and Nvidia Toronto AI lab led by Prof. Sanja Fidler. I also spent time as a research student at Data-Driven Decision Making Lab led by Prof. Scott Sanner.
I'm generally interested in machine learning, reinforcement learning, and robotics. My current research focus is on safe RL and transfer learning in RL (specifically in Sim-to-Real applications).
I worked as a deep learning intern and focused on synthetic data generation for computer vision tasks in autonomous driving. I also worked on trajectory prediction, graph neural networks, and distribution matching on videos.
We propose safe-control-gym as a benchmark suite for safe-learning in robotics. It implements several PyBullet-based benchmark environments and control algorithms from traditional control, safe-learning control, safe RL, robust RL.
RL transfer learning baselines are recently added.
We conduct an extensive review on safe-learning-based methods in robotics, and provides a formulation of safe-learning-control to bridge between control theory and reinforcement learning. We also show safe control examples to highlight the need for a safety benchmark.
We propose Meta-Sim, which learns a generative model of synthetic scenes with the help of a graphics engine. It minimizes the distribution gap between synthetic images and real images. Experiments show that Meta-Sim can greatly improve scene quality and help in downstream task training.
We provide the full description of safe-control-gym and use it to perform in-depth benchmarks over RL baselines regarding three aspects of safety in robot control. We also propose useful practices to design safe agents by looking at their respective ablations.
We investigate the emergent behaviors in Multi-agent Reinforcement Learning (MARL) with the OpenAI MPE environment. From experiments, we discover that meaningful team collaboration and communication protocols can be learned.
More About Me
I am especially interested in the intersection of machine learning and simulation technologies, with notable applications such as gaming and robotics (a possible influence from the Matrix Trilogy).
Besides doing research and programming, I also enjoy reading, pop music, and anime in my free time. My go-to relaxation at the weekend would often be a new chapter of One Piece plus loop-over some music top charts.