Carl Qi

Carl (Hanwen) Qi

I am a Ph.D. student at the University of Texas at Austin, where I am advised by Prof. Amy Zhang in Machine Intelligence through Decision-making and Interaction (MIDI) Lab.

Pror to UT, I obtained my Master's degree at CMU, where I was advised by Prof. David Held. I obtained my undergraduate degree in CS and Applied Math at UC Berkeley, where I was fortunate to work with Prof. Pieter Abbeel and Prof. Aditya Grover in Robot Learning Lab (RLL).

carlq@utexas.edu / CV / LinkedIn / Google Scholar

Research

I'm broadly interested in Reinforcement Learning, Computer Vision, and Robotics. My specific interests include representation learning, long-horizon reasoning, and multi-task learning. My long-term research goal is to allow autonomous agents to act and learn in unstructured real world environments.

	EC-Diffuser: Multi-Object Manipulation via Entity-Centric Behavior Generation Carl Qi, Dan Haramati, Tal Daniel, Aviv Tamar, Amy Zhang Preprint, 2024 Paper / Project Page
	Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning Caleb Chuck, Carl Qi, Michael Joseph Munje, Shuozhe Li, Max Rudolph, Chang Shi, Siddhant Agarwal, Harshit Sikchi, Abhinav Peri, Sarthak Dayal, Evan Kuo, Kavan Mehta, Anthony Wang, Peter Stone, Amy Zhang, Scott Niekum ICRA Workshop Manipulation Skills, 2024 Paper / Project Page / Code (coming soon)
	Learning Generalizable Tool-use Skills through Trajectory Generation Carl Qi, Yilin Wu, Lifan Yu, Haoyue, Liu, Bowen Jiang, Xingyu Lin, David Held IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024 Paper / Project Page / Code (coming soon)
	Planning with Spatial-Temporal Abstraction from Point Clouds for Deformable Object Manipulation Xingyu Lin, Carl Qi, Yunchu Zhang, Zhiao Huang, Katerina Fragkiadaki, Yunzhu Li, Chuang Gan, David Held Conference on Robot Learning (CoRL), 2022 Paper / OpenReview / Project Page / Code
	Learning Closed-loop Dough Manipulation using a Differentiable Reset Module Carl Qi, Xingyu Lin, David Held IEEE Robotics and Automation Letters (RA-L), 2022 Paper / Project Page / Code Covered by [The Washington Post] [CMU SCS News (robots roll dough)]
	Imitating, Fast and Slow: Robust learning from demonstrations via decision-time planning Carl Qi, Pieter Abbeel, Aditya Grover Preprint, 2022 Paper

Teaching

	TA, 10-418/618: ML for Structured Data, Spring 2022 TA, 10-725: Convex Optimization, Fall 2021
	Instructor, CS188: Artificial Intelligence, Summer 2021 TA, CS188: Artificial Intelligence, Spring 2021 TA, CS188: Artificial Intelligence, Fall 2020 TA, CS188: Artificial Intelligence, Spring 2020 TA, CS188: Artificial Intelligence, Fall 2019

Website source taken from here.