Krishna Murthy Jatavallabhula (Preferred)
, J. Krishna Murthy
, Krishna Murthy
Krishna Murthy Jatavallabhula
Massachusetts 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.
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.
****@gmail.com
, ****@pilani.bits-pilani.ac.in
, ****@research.iiit.ac.in
, ****@mila.quebec
, ****@mit.edu
Personal Links
Add links to your profiles on other sites. (Optional)
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.
Postdoc
Massachusetts Institute of Technology (mit.edu)
2022 – Present
PhD student
University of Montreal (umontreal.ca)
2018 – Present
Intern
NVIDIA (nvidia.com)
2019 – 2020
MS student
IIIT Hyderabad (research.iiit.ac.in)
2015 – 2017
Undergrad student
BITS Pilani (pilani.bits-pilani.ac.in)
2011 – 2015
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Postdoc Advisor
Joshua Tenenbaum
****@mit.edu
2022 – Present
Postdoc Advisor
Antonio Torralba
****@csail.mit.edu
2022 – Present
Coauthor
Ganesh Iyer
****@gmail.com
2017 – Present
Coauthor
Gunshi Gupta
****@gmail.com
2017 – Present
Self
Krishna Murthy Jatavallabhula
****@gmail.com
2015 – Present
PhD Advisor
Liam Paull
****@iro.umontreal.ca
2018 – 2022
Coauthor
Sanja Fidler
****@cs.utoronto.edu
2019 – 2021
MS Advisor
Madhava Krishna K
****@iiit.ac.in
2015 – 2018
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
SLAM, Embodied agents, Differentiable physics, Robotics, Task planning, Differentiable rendering, Deep Learning, Structure from Motion
Present