Google Research

Boqing Gong

About

Boqing Gong is a research scientist at Google, Seattle. His research in machine learning and computer vision focuses on sample-efficient learning (e.g., domain adaptation, few-shot, reinforcement, webly-supervised, and self-supervised learning) and the visual analytics of objects, scenes, human activities, and their attributes. Before joining Google in 2019, he worked in Tencent and was a tenure-track Assistant Professor at the University of Central Florida (UCF). He received an NSF CRII award in 2016 and an NSF BIGDATA award in 2017, both of which were the first of their kinds ever granted to UCF. He is/was a (senior) area chair of NeurIPS, ICML, CVPR, ICCV, ECCV, AAAI, AISTATS, and WACV. He received his Ph.D. in 2015 at the University of Southern California, where the Viterbi Fellowship partially supported his work.

Please visit http://boqinggong.info/ for more information.

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