Chong You
Chong You
Names
How do you usually write your name as author of a paper? Also add any other names you have authored papers under.
Emails
Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.
****@cis.jhu.edu
, ****@gmail.com
, ****@berkeley.edu
, ****@google.com
Personal Links
Add links to your profiles on other sites. (Optional)
Education & Career History
Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.
Research Scientist
Google (google.com)
2021 – Present
Postdoc
University of California Berkeley (berkeley.edu)
2018 – 2021
PhD student
Johns Hopkins University (jhu.edu)
2012 – 2018
MS student
Peking University (pku.edu.cn)
2009 – 2012
Undergrad student
Peking University (pku.edu.cn)
2005 – 2009
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coauthor
Zhihui Zhu
****@du.edu
2020 – Present
Coauthor
Qing Qu
****@umich.edu
2020 – Present
Coauthor
Ben Haeffele
****@jhu.edu
2020 – Present
Coauthor
Jeremias Sulam
****@jhu.edu
2020 – Present
Coauthor
Chun-guang Li
****@bupt.edu.cn
2014 – Present
Coauthor
John Wright
****@ee.columbia.edu
2021 – 2021
Postdoc Advisor
Yi Ma
****@eecs.berkeley.edu
2018 – 2021
Coauthor
Jacob Steinhardt
****@berkeley.edu
2020 – 2020
Coauthor
Xiaolong Wang
****@eng.ucsd.edu
2020 – 2020
Coauthor
Zhouchen Lin
****@pku.edu.cn
2019 – 2019
PhD Advisor
Daniel P. Robinson
****@lehigh.edu
2015 – 2018
PhD Advisor
Rene Vidal
****@cis.jhu.edu
2012 – 2018
Expertise
For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing
deep learning, implicit regularization, architectural design
2019 – Present
subspace clustering, sparse representation, image clustering
2014 – Present