Bogdan Kulynych (Preferred)
Bogdan Kulynych
EPFL
Names
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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.
****@epfl.ch
, ****@kulyny.ch
Personal Links
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Education & Career History
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PhD student
EPFL (epfl.ch)
Present
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
PhD Advisor
Carmela Troncoso
****@epfl.ch
2018 – Present
Coworker
Flavio Calmon
****@seas.harvard.edu
2022 – 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
predictive multiplicity
2022 – Present
membership inference attacks
2019 – Present
algorithmic fairness
2018 – Present
trustworthy machine learning
2018 – Present