Faculty Candidate Seminar

Towards Embodied Visual Intelligence

Dinesh Jayaraman

University of California, Berkeley
Monday, February 04, 2019
10:30am - 11:30am
3725 Beyster

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About the Event

Joint CSE/ECE Faculty Candidate Seminar

What would it mean for a machine to see the world? Computer vision has recently made great progress on problems such as finding categories of objects and scenes, and poses of people in images. However, studying such tasks in isolated disembodied contexts, divorced from the physical source of their images, is insufficient to build intelligent visual agents. My research focuses on remarrying vision to action, by asking: how might vision benefit from the ability to act in the world, and vice versa? Could embodied visual agents teach themselves through interaction and experimentation? Are there actions they might perform to improve their visual perception? Could they exploit vision to perform complex control tasks? In my talk, I will set up the context for these questions, and cover some strands of my work addressing them, proposing approaches for self-supervised learning through proprioception, visual prediction for decomposing complex control tasks, and active perception. Finally, I will discuss my long-term vision and directions that I hope to work on in the next several years.


Dinesh Jayaraman is a postdoctoral scholar in EECS at UC Berkeley. He received his PhD from UT Austin (2017) and B. Tech from IIT Madras (2011). His research interests are broadly in computer vision, robotics, and machine learning. In the last few years, he has worked on visual prediction, active perception and visual learning in embodied agents, visuo-tactile robotic manipulation, semantic visual attributes, and zero-shot categorization. His work has been recognized with the ACCV Best Application Paper Award (2016), a Samsung PhD Fellowship (2016), a UT Austin Graduate Dean's Prestigious Fellowship (2016), and a UT Austin Microelectronics and Computer Development Fellowship Award (2011). He reviews for top conferences and journals across computer vision, machine learning, and robotics, won a CVPR Outstanding Reviewer Award (2016), and served as an Area Chair for NIPS 2018.

Additional Information

Sponsor(s): CSE

Open to: Public