(Cannon Beach, Oregon)
My early research involved various topics such as object segmentation, language grounding in video, video captioning , embodied language understanding, and the lottery ticket hypothesis. Since joining Horizon Robotics in 2019, I've been working on learning-based robotics problems such as hierarchical RL, safe/constrained RL, and exploration.
I love writing code and building things. I am a co-author and an active maintainer of the RL framework ALF that supports most RL research at Horizon.
My current passion is to combine all my past experience on language grounding, video understanding, and learning-based robotic control, to build an agile robot that takes natural language commands in indoor scenarios with strong generalization capabilities.
|Ph.D. of Electrical and Computer Engineering (ECE), Purdue University|
|Bachelor of Computer Science (CS), Peking University|
ALF - Agent Learning Framework
(ALF) is a PyTorch reinforcement learning framework emphasizing on the flexibility
and easiness of implementing complex algorithms involving many different
TAAC - Temporally abstract actor-critic algorithm for efficient continuous control.
XWorld - A simulator package for RL research with language task support.
FLARE - A reinforcement learning framework for training embodied agents with PyTorch.
I like playing video games, especially ARPG. So far my favorite games are souls-like, by FromSoftware.