Amir-massoud Farahmand

Department of Computer Science, University of Toronto

Names

How do you usually write your name as author of a paper? Also add any other names you have authored papers under.

Amir-massoud Farahmand (Preferred)

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.

****@merl.com
,
****@ualberta.ca
,
****@vectorinstitute.ai

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.

Assistant Professor
Department of Computer Science, University of Toronto (cs.toronto.edu)
2019Present
 
Faculty Member
Vector Institute (vectorinstitute.ai)
2018Present
 
Principal Research Scientist
Mitsubishi Electric Research Laboratories (MERL) (merl.com)
20142018
 
Postdoc
Carnegie Mellon University (cmu.edu)
20142014
 
Postdoc
McGill University (mcgill.ca)
20112014
 
PhD student
University of Alberta (ualberta.ca)
20052011
 

Advisors, Relations & Conflicts

Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.

Coauthor
Martha White
****@ualberta.ca
2017Present
 
PhD Advisee
Yangchen Pan
****@ualberta.ca
2017Present
 
Coauthor
Mohammad Ghavamzadeh
****@gmail.com
2005Present
 
Coworker
Daniel Nikovski
****@merl.com
20142018
 
Postdoc Advisor
J. Andrew Bagnell
****@ri.cmu.edu
20142014
 
Postdoc Advisor
Doina Precup
****@cs.mcgill.ca
20112014
 
PhD Advisor
Csaba Szepesvari
****@ualberta.ca
20062011
 

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

reinforcement learning, statistical learning theory, nonparametric estimators
Present