Bio

I lead the Visual Information and Dynamics team, a computer vision research group at Google AI. Our goal is to discover new ways to understand video, with an emphasis on objects, motion, and actions. The team's work includes the Tensorflow Object Detection API, as well as models that help power personal video understanding in Google Photos and Cloud Video Intelligence. We publish research at top academic conferences including CVPR, and organize the AVA Challenge to advance state-of-the-art spatiotemporal action recognition in video.

Previously I lead the YouTube Mix team that built the personalized algorithmic radio feature at the heart of YouTube Music.

I obtained my Ph.D. in Machine Learning and Computer vision from the University of Toronto, Canada.

Current Work

Publications

Code

Other Stuff