Animesh Garg

Georgia Institute of Technology

Names

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

Animesh Garg (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.

****@cs.stanford.edu
,
****@cs.toronto.edu
,
****@gmail.com
,
****@nvidia.com
,
****@utoronto.ca
,
****@gatech.edu
,
****@berkeley.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
Georgia Institute of Technology (gatech.edu)
2023Present
 
Researcher
NVIDIA (nvidia.com)
2018Present
 
Assistant Professor
University of Toronto (toronto.edu)
20192023
 
Postdoc
Stanford University (stanford.edu)
20162018
 
PhD student
University of California Berkeley (berkeley.edu)
20112016
 
MS student
Georgia Institute of Technology (gatech.edu)
20102011
 

Advisors, Relations & Conflicts

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

Coworker
Anima Anandkumar
****@nvidia.com
2018Present
 
Coworker
Dieter Fox
****@nvidia.com
2018Present
 
Coworker
Sanja Fidler
****@nvidia.com
2018Present
 
Postdoc Advisor
Fei-Fei Li
****@cs.stanford.edu
20162018
 
Postdoc Advisor
Silvio Savarese
****@stanford.edu
20162018
 
PhD Advisor
Ken Goldberg
****@berkeley.edu
20112016
 
PhD Advisor
Pieter Abbeel
****@cs.berkeley.edu
20112016
 

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

Causal Inference
2018Present
 
3D Vision
2017Present
 
Representation Learning
2016Present
 
Computer Vision
2016Present
 
Reinforcement Learning
2014Present
 
Robot Learning
2014Present
 
Robotics
2011Present