Ching-An Cheng


Hometown: Taichung, Taiwan
Georgia Institute of Technology

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Research: Ching-An Cheng is interested in developing the theoretical foundations for efficient and principled robot learning. His current research focus concerns sample efficiency, structural properties, and uncertainty in robot learning. Specific topics include reinforcement learning, imitation learning, online learning, meta learning, (large-scale) Gaussian processes, and integrated motion planning and control.

Ching-An Cheng is a Robotics PhD student advised by Byron Boots in the Institute for Robotics and Intelligent Machines at Georgia Tech. His research lies in the intersection between machine learning, optimization, and control theory. Before joining Georgia Tech, he studied at the National Taiwan University where he received a double degree consisting of a B.S. in Mechanical Engineering and B.S. in Electrical Engineering, and an M.S. in Mechanical Engineering. His work has won several awards including the Best Paper Award at AISTATS 2018 and Finalist for Best Systems Paper Award at RSS 2018.