Warren Richard Morningstar (Preferred)
Warren Richard Morningstar
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.
****@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.
Senior Software Engineer
Google (google.com)
2023 – Present
Software Engineer
Google (google.com)
2021 – 2023
Postdoc
Google (google.com)
2019 – 2021
PhD student
Stanford University (stanford.edu)
2014 – 2019
Undergrad student
University of Michigan (umich.edu)
2009 – 2013
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coworker
Tao Tu
****@google.com
2023 – 2023
Coworker
Elahe Vedadi
****@google.com
2023 – 2023
Coworker
Chris Duvarney
****@google.com
2023 – 2023
Coworker
Khaled Saab
****@google.com
2023 – 2023
Coauthor
Renan Rojas Gomez
****@illinois.edu
2023 – 2023
Coauthor
Neha Kalibhat
****@umd.edu
2023 – 2023
Coworker
Philip Mansfield
****@google.com
2022 – 2023
Coworker
Karan Singhal
****@google.com
2021 – 2023
Coworker
Josh Dillon
****@google.com
2019 – 2023
Coworker
Alex Alemi
****@google.com
2019 – 2023
PhD Advisor
Roger Blandford
****@stanford.edu
2014 – 2019
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
Self Supervised Learning
2021 – 2023
Computer Vision
2019 – 2023
Deep Learning
2015 – 2023