Deepak Pathak

Carnegie Mellon University

Names

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

Deepak Pathak

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.

****@berkeley.edu
,
****@cs.berkeley.edu
,
****@fb.com
,
****@cs.cmu.edu
,
****@andrew.cmu.edu

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
Carnegie Mellon University (cmu.edu)
2020Present
 
Researcher
Facebook AI Research (fb.com)
20192020
 
Visiting Researcher
University of California Berkeley (berkeley.edu)
20192020
 
PhD student
University of California Berkeley (berkeley.edu)
20142019
 

Advisors, Relations & Conflicts

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

PhD Advisor
Trevor Darrell
****@eecs.berkeley.edu
20142019
 
PhD Advisor
Alexei A. Efros
****@eecs.berkeley.edu
20142019
 
Coauthor
Philipp Kraehenbuehl
****@berkeley.edu
20152016
 
Coauthor
Judy Hoffman
****@cs.stanford.edu
20142015
 
Coauthor
Kate Saenko
****@cs.uml.edu
20112015
 
Coauthor
Evan Shelhamer
****@eecs.berkeley.edu
20142014
 
Coauthor
Kate Saenko
****@eecs.berkeley.edu
20142014
 
Coauthor
Trevor Darrell
****@eecs.berkeley.edu
20112014
 
Coauthor
Amitabha Mukerjee
****@iitk.ac.in
20112014
 
Coauthor
Judy Hoffman
****@eecs.berkeley.edu
20112014
 
Coauthor
Jonathan Long
****@cs.berkeley.edu
20112014
 

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

deep learning
2014Present
 
reinforcement learning
2014Present
 
computer vision
2014Present
 
robotics
2014Present