Mrinal Kalakrishnan

Researcher, Meta

Joined

September 2017

Names

Mrinal Kalakrishnan

Emails

****@mrinal.net (Confirmed)

****@google.com (Confirmed)

****@x.team (Confirmed)

****@everydayrobots.com (Confirmed)

****@meta.com (Confirmed)

Personal Links

Google Scholar

DBLP

Career & Education History

Researcher

Meta (meta.com)

2022 – Present

Roboticist

Everyday Robots (everydayrobots.com)

2021 – 2022

Roboticist

X (x.team)

2016 – 2022

Roboticist

Google (google.com)

2014 – 2022

PhD student

University of Southern California (usc.edu)

2008 – 2013

Advisors, Relations & Conflicts

PhD Advisor

Stefan Schaal

2008 – 2013

Expertise

reinforcement learning

imitation learning

robotics

Present

Publications

LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Paul McVay, Sergio Arnaud, Ada Martin, Arjun Majumdar, Krishna Murthy Jatavallabhula, Phillip Thomas, Ruslan Partsey, Daniel Dugas, Abha Gejji, Alexander Sax, Vincent-Pierre Berges, Mikael Henaff, Ayush Jain, Ang Cao, Ishita Prasad, Mrinal Kalakrishnan, Michael Rabbat, Nicolas Ballas, Mido Assran, Oleksandr Maksymets et al. (2 additional authors not shown)
- ICML 2025 spotlightposter
- Readers: Everyone
Sparsh: Self-supervised touch representations for vision-based tactile sensing
Carolina Higuera, Akash Sharma, Chaithanya Krishna Bodduluri, Taosha Fan, Patrick Lancaster, Mrinal Kalakrishnan, Michael Kaess, Byron Boots, Mike Lambeta, Tingfan Wu, Mustafa Mukadam
- CoRL 2024
- Readers: Everyone
OpenEQA: Embodied Question Answering in the Era of Foundation Models
Arjun Majumdar, Anurag Ajay, Xiaohan Zhang, Pranav Putta, Sriram Yenamandra, Mikael Henaff, Sneha Silwal, Paul McVay, Oleksandr Maksymets, Sergio Arnaud, Karmesh Yadav, Qiyang Li, Benjamin Newman, Mohit Sharma, Vincent-Pierre Berges, Shiqi Zhang, Pulkit Agrawal, Yonatan Bisk, Dhruv Batra, Mrinal Kalakrishnan et al. (4 additional authors not shown)
- MoMa WS 2024 Oral
- Readers: Everyone
What Do We Learn from a Large-Scale Study of Pre-Trained Visual Representations in Sim and Real Environments?
Sneha Silwal, Karmesh Yadav, Tingfan Wu, Jay Vakil, Arjun Majumdar, Sergio Arnaud, Claire Chen, Vincent-Pierre Berges, Dhruv Batra, Aravind Rajeswaran, Mrinal Kalakrishnan, Franziska Meier, Oleksandr Maksymets
- MoMa WS 2024 Oral
- Readers: Everyone
Habitat 3.0: A Co-Habitat for Humans, Avatars, and Robots
Xavier Puig, Eric Undersander, Andrew Szot, Mikael Dallaire Cote, Tsung-Yen Yang, Ruslan Partsey, Ruta Desai, Alexander Clegg, Michal Hlavac, So Yeon Min, Vladimír Vondruš, Theophile Gervet, Vincent-Pierre Berges, John M Turner, Oleksandr Maksymets, Zsolt Kira, Mrinal Kalakrishnan, Jitendra Malik, Devendra Singh Chaplot, Unnat Jain et al. (3 additional authors not shown)
- ICLR 2024 poster
- Readers: Everyone
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
Alexander Herzog, Kanishka Rao, Karol Hausman, Yao Lu, Paul Wohlhart, Mengyuan Yan, Jessica Lin, Montserrat Gonzalez Arenas, Ted Xiao, Daniel Kappler, Daniel Ho, Jarek Rettinghouse, Yevgen Chebotar, Kuang-Huei Lee, Keerthana Gopalakrishnan, Ryan Julian, Adrian Li, Chuyuan Kelly Fu, Bob Wei, Sangeetha Ramesh et al. (20 additional authors not shown)
- Published: 01 Jan 2023, Last Modified: 12 May 2023
- CoRR 2023
- Readers: Everyone
USA-Net: Unified Semantic and Affordance Representations for Robot Memory
Benjamin Bolte, Austin Wang, Jimmy Yang, Mustafa Mukadam, Mrinal Kalakrishnan, Chris Paxton
- Published: 01 Jan 2023, Last Modified: 05 Jun 2023
- CoRR 2023
- Readers: Everyone
How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned
Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine
- 2021 (modified: 12 May 2023)
- CoRR 2021
- Readers: Everyone
How to train your robot with deep reinforcement learning: lessons we have learned
Julian Ibarz, Jie Tan, Chelsea Finn, Mrinal Kalakrishnan, Peter Pastor, Sergey Levine
- 2021 (modified: 11 Apr 2023)
- Int. J. Robotics Res. 2021
- Readers: Everyone
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards
Allan Zhou, Eric Jang, Daniel Kappler, Alexander Herzog, Mohi Khansari, Paul Wohlhart, Yunfei Bai, Mrinal Kalakrishnan, Sergey Levine, Chelsea Finn
- 2020 (modified: 15 Nov 2022)
- ICLR 2020
- Readers: Everyone

View all 56 publications

Co-Authors

View all 156 co-authors