Timnit Gebru (Preferred)
Timnit Gebru
Distributed AI Research Institute (DAIR)
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.
****@gmail.com
, ****@stanford.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.
Researcher
Distributed AI Research Institute (DAIR) (dair-institute.org)
2021 – Present
Research Scientist
Google AI (google.com)
2018 – 2020
Postdoc
Microsoft Research (microsoft.com)
2017 – 2018
PhD student
Stanford University (stanford.edu)
2011 – 2017
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coworker
margaret mitchell
****@google.com
2018 – Present
former coworker
hanna wallach
****@dirichlet.net
2017 – 2018
Coworker
hal daume III
****@microsoft.com
2017 – 2018
Coworker
Jenn Wortman-Vaughn
****@microsoft.com
2017 – 2018
Coauthor
Jia Deng
****@umich.edu
2014 – 2017
PhD Advisor
fei-fei li
****@cs.stanford.edu
2013 – 2017
Advisor
Fei-fei Li
****@cs.stanford.edu
2013 – 2017
Coauthor
Jonathan Krause
****@cs.stanford.edu
2014 – 2014
Coauthor
Jia Deng
****@cs.stanford.edu
2014 – 2014
Coauthor
Li-jia Li
****@gmail.com
2011 – 2014
Coauthor
Jia Deng
****@umich.edu
2011 – 2014
Coauthor
Li-jia Li
****@cs.stanford.edu
2011 – 2014
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
Fairness Accountability Transparency and Ethics
Present
Domain Adaptation
2015 – Present
Responsible AI
2015 – Present
Dataset collection, annotation, curation
2013 – Present