I am a research scientist in
the newly founded Intel Visual Computing Lab.
I completed my
Computer Sciences at the University of Wisconsin-Madison in July 2015,
with my thesis committee of Prof. Vikas Singh (advisor),
Prof. Chuck Dyer,
Prof. Jerry Zhu,
Prof. Jude Shavlik, and
Prof. Mark Craven.
I was a visiting student in University of Toronto during summer 2014, and in
Toyota Technological Institute at Chicago during Summer 2013,
both working with Prof. Raquel Urtasun.
In the first year (2010-2011) of my graduate study, I worked as a research assistant/intern at Epic.
Before graduate school, I obtained my B.S. degree from
the Department of Computer Science and Technology
University, China in June 2010.
Curriculum Vitae (pdf).
My major interests are computer vision, deep learning, and optimization.
In particular, I am interested in systematically building reliable visual perception algorithms (e.g., semantic segmentation, dense correspondence, video analytics/segmentation) by
mathematically modeling the physical properties of visual data (e.g., geometry, structure, context),
and learning from the massive unlabeled or weakly labeled data available on the Internet.
My ultimate research goal is to enable computers to perceive
and reason at/beyond human level.
Our Fast Image Processing paper is accepted to
Our DCFlow paper is accepted to
CVPR 2017. Currently #1 on the Sintel Optical Flow Benchmark.