Zhao Song (Preferred)
Zhao Song
Adobe Research
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.
****@uw.edu
, ****@gmail.com
, ****@utexas.edu
, ****@princeton.edu
, ****@adobe.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.
Researcher
Adobe Research (adobe.com)
2021 – Present
Postdoc
Princeton University (princeton.edu)
2020 – 2021
Postdoc
Institue for Advanced Study, Princeton (ias.edu)
2019 – 2020
Intern
The University of Washington (cs.washington.edu)
2018 – 2019
Intern
Research, Microsoft (research.microsoft.com)
2018 – 2019
Intern
Simons at University of California, Berkeley (berkeley.edu)
2018 – 2019
PhD student
University of Texas at Austin (utexas.edu)
2014 – 2019
Intern
Harvard University (harvard.edu)
2017 – 2018
Intern
Research, IBM (us.ibm.com)
2015 – 2017
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Postdoc Advisor
Sanjeev Arora
****@cs.princeton.edu
2019 – 2021
PhD Advisor
Zeyuan Allen-Zhu
****@csail.mit.edu
2018 – 2019
PhD Advisor
Yin Tat Lee
****@uw.edu
2018 – 2019
PhD Advisor
Eric Price
****@cs.utexas.edu
2014 – 2019
PhD Advisor
Jelani Nelson
****@berkeley.edu
2017 – 2018
PhD Advisor
David P. Woodruff
****@andrew.cmu.edu
2015 – 2017
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
Theory
Present