Peter Y. Lu (Preferred)
, Peter Y Lu
Peter Y. Lu
University of Chicago
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.
****@mit.edu
, ****@gmail.com
, ****@uchicago.edu
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.
Postdoc
University of Chicago (uchicago.edu)
2022 – Present
PhD student
Massachusetts Institute of Technology (mit.edu)
2016 – 2022
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Postdoc Advisor
Vincenzo Vitelli
****@uchicago.edu
2023 – Present
Postdoc Advisor
Rebecca Willett
****@uchicago.edu
2022 – Present
Coauthor
Ruoxi Jiang
****@uchicago.edu
2022 – Present
Coauthor
Elena Orlova
****@uchicago.edu
2022 – Present
PhD Advisor
Marin Soljacic
****@mit.edu
2016 – Present
Coauthor
Charlotte Loh
****@mit.edu
2016 – Present
Coworker
Rumen Dangovski
****@mit.edu
2016 – Present
Coauthor
Oreoluwa Alao
****@mit.edu
2016 – Present
Coauthor
Owen Dugan
****@mit.edu
2016 – Present
Coauthor
Di Luo
****@mit.edu
2016 – Present
Coauthor
Ali Cy
****@mit.edu
2016 – Present
Coauthor
Samuel Kim
****@mit.edu
2016 – 2022
Coauthor
Jasper Snoek
****@google.com
2016 – 2022
Coauthor
Jamie Smith
****@google.com
2016 – 2022
Coworker
Ileana Rugina
****@mit.edu
2016 – 2022
Coworker
Andrew Ma
****@mit.edu
2016 – 2022
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
condensed matter physics, machine learning
Present
nonlinear dynamics, machine learning
Present
physics, machine learning
Present