Eleni Triantafillou
Eleni Triantafillou
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.
****@cs.toronto.edu
, ****@gmail.com
, ****@google.com
Personal Links
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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
Google (google.com)
2021 – Present
PhD student
University of Toronto (toronto.edu)
2017 – 2021
Intern, student researcher
Google (google.com)
2019 – 2019
Intern
Microsoft (microsoft.com)
2015 – 2015
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coauthor
Vincent Dumoulin
****@google.com
2018 – Present
Coauthor
Utku Evci
****@google.com
2018 – Present
Coauthor
Pascal Lamblin
****@google.com
2018 – Present
Coauthor
Ross Goroshin
****@google.com
2018 – Present
Coauthor
Tyler Zhu
****@google.com
2018 – Present
Coauthor
Pierre-Antoine Manzagol
****@google.com
2018 – Present
Coauthor
Mengye Ren
****@cs.toronto.edu
2017 – Present
Coauthor
Jake Snell
****@cs.toronto.edu
2017 – Present
Coauthor
Hugo Larochelle
****@google.com
2017 – Present
Coauthor
Kevin Swersky
****@google.com
2017 – Present
PhD Advisor
Richard Zemel
****@cs.toronto.edu
2016 – 2021
PhD Advisor
Raquel Urtasun
****@cs.toronto.edu
2016 – 2021
Coauthor
Kelvin Xu
****@berkeley.edu
2018 – 2019
Coauthor
Sachin Ravi
****@princeton.edu
2017 – 2019
Coauthor
Josh B. Tenenbaum
****@mit.edu
2017 – 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
few-shot learning, transfer learning, self-supervised learning, domain generalization, domain adaptation
2021 – Present
few-shot learning, meta-learning
2016 – Present
natural language processing, sentence representation learning
2016 – 2017