[Colloquium] 3/24 Talks at TTIC: Kuan Fang, UC Berkeley

[Mary Marre]

*When:*        Friday, March 24, 2023 at* 11:00** a**m CT   *


*Where:       *Talk will be given *live, in-person* at

                   TTIC, 6045 S. Kenwood Avenue

                   5th Floor, Room 530


*Virtually:*  *via* Panopto (*livestream
<https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=d9e7109f-b795-49fb-b3fd-afc801562270>*
)


*Who: *         Kuan Fang, UC Berkeley


------------------------------
*Title: *Scalable Robot Intelligence: Self-Supervised Learning through
Generation

*Abstract: *Rapid advances in deep learning have resulted in promising
techniques for robots to boost their capabilities to perceive, reason, and
act by leveraging large models and massive datasets. However, the
scalability of existing robot learning methods is severely limited by the
manual labor and domain knowledge that humans can provide. To acquire
general-purpose skills for solving a broad range of tasks, intelligent
robots need scalable methods to collect and learn from rich data without
extensive human supervision.

In this talk, I will present my research on scaling up robot learning
through the autonomous generation of environments, goals, and tasks. I will
start by describing how to leverage procedural content generation for
learning robust skills that can handle the variety and uncertainty of the
real world. Then I will present algorithms that train robots to effectively
reuse skills learned from prior experiences for novel sequential tasks by
learning to generate reachable subgoals. Finally, I will demonstrate how to
enable robots to discover a repertoire of novel skills by adaptively
generating tasks during training. The acquired skills can be used for
solving a variety of complex tasks such as tool use and sequential
manipulation based on raw sensory inputs.

*Bio: *Kuan Fang is a postdoctoral researcher in the Department of
Electrical Engineering and Computer Sciences at UC Berkeley, working with
Sergey Levine. He received his Ph.D. degree in Electrical Engineering from
Stanford University, advised by Fei-Fei Li and Silvio Savarese. His
research interests lie at the intersection of robotics, computer vision,
and machine learning, with a focus on developing data-driven methods to
enable intelligent robots to operate in unstructured environments. He is a
recipient of the Stanford Graduate Fellowship and the Computing Innovation
Fellowship.

*Host: *Matthew Walter <mwalter at ttic.edu>




Mary C. Marre
Faculty Administrative Support
*Toyota Technological Institute*
*6045 S. Kenwood Avenue, Rm 517*
*Chicago, IL  60637*
*773-834-1757*
*mmarre at ttic.edu <mmarre at ttic.edu>*
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