About Me

At Facebook AI Research (FAIR) I work on research problems in computer vision, deep learning, reinforcement learning. I also enjoy building powerful frameworks and infrastructure for research, such as detectron2 and tensorpack.

Education

  • Master in Computer Vision, 2016

    Carnegie Mellon University

  • Bachelor in Computer Science, 2015

    Tsinghua University

Selected Publications

Momentum Contrast for Unsupervised Visual Representation Learning

Computer Vision and Pattern Recognition (CVPR), 2020 (Oral)
Best Paper Nomination (top 30)

PointRend: Image Segmentation as Rendering

Computer Vision and Pattern Recognition (CVPR), 2020 (Oral)

Feature Denoising for Improving Adversarial Robustness

The first ImageNet classifier that survives strong white-box adversarial attacks.
Computer Vision and Pattern Recognition (CVPR), 2019

Group Normalization

A batch-independent alternative to Batch Normalization.
European Conference on Computer Vision (ECCV), 2018 (Oral)
Best Paper Honorable Mention (top 3)

House3D: A Rich and Realistic 3D Environment

International Conference on Learning Representations (ICLR), 2018

ELF: An Extensive, Lightweight and Flexible Research Platform for Real-time Strategy Games

Platform that powers large-scale RL projects such as OpenGO.
Neural Information Processing Systems (NeurIPS), 2017 (Oral)

Open Source Projects

More at github.

Detectron2

Research platform & production library for object detection, segmentation, and more. Widely used in research community and dozens of Facebook products & services.

Tensorpack

A neural net training interface on TensorFlow, with focus on speed + flexibility.

Adversarial Attack on Face Recognition

Black-box adversarial attacks on AWS/Azure’s public face recognition APIs, the first successful attack of its kind.

OpenPano

Panorama stitching written from scratch in C++.

wechat-dump

Cracking encrypted wechat message history from Android phones by reverse-engineering.

Work Experience

 
 
 
 
 

Research Engineer

Facebook AI Research

March 2017 – Present Menlo Park
Build systems and perform research in computer vision & reinforcement learning.
 
 
 
 
 

Research Assistant

Oculus Research

January 2016 – April 2016 Pittsburgh
Research about face modeling and GANs towards VR avatars.
 
 
 
 
 

Researcher

Megvii (aka Face++)

October 2014 – August 2015 Beijing
In-house deep learning training framework.
Research & products in computer vision, including OCR, model quantization, etc.
 
 
 
 
 

Software Engineering Intern

Google

April 2014 – July 2014 Beijing
SfM (structure from motion) from videos.

Awards

  • Winner of defense track in Competition on Adversarial Attacks and Defenses (CAAD) 2018.

    We trained an ImageNet classifier with state-of-the-art robustness against adversarial attacks. Competition

  • Winner of CTF in Competition on Adversarial Attacks and Defenses (CAAD) CTF 2018.

    We performed successful adversarial attacks / defenses against other teams during the on-site competition. Competition Media (Chinese)

  • Best Paper Honorable Mention award in ECCV 2018. Announcement

  • Google Open Source Peer Bonus in 2017. Announcement

  • Winner of VizDoom AI Competition in CIG 2016.

    Our Doom bot, “F1”, beat all other competitors in a death match by a large margin. Competition Media Video

  • Champion of Student Cluster Competition in both ISC 2015 and ASC 2015.

    Optimize software and hardware for low-power high-performance computation. Media Media

  • Finalist in SIGMOD Programming Contest in SIGMOD 2014, as team leader of “blxlrsmb”.

    Design and implement a large social network database to support efficient queries. Competition Slides Poster

  • Capture the Flags (CTF, a form of security competition): 11th in SECCON CTF 2014, 8th in Codegate CTF 2015, 5th in DEFCON CTF 2015 as a team member of “blue-lotus”.