Jay Darshan Vakil

About me

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I am a Robotics Engineer at Facebook AI Research (FAIR) with the Embodied AI team. I build efficient large-scale artificial agents that learn from structured visual world representations to solve multi-task, non-trivial manipulation problems. I am mentored by Vikash Kumar, Franziska Meier, and Chris Paxton and collaborate closely with Homanga Bharadhwaj and Sergio Arnaud.

I earned my Bachelor of Science in Electrical Engineering with a Computer Science and Math minor from the University of Washington.

I am interested in areas of Robotics, Embodied Artificial Intelligence (EAI), and solving autonomous world navigation. Besides robotics and research, I am interested in climbing/bouldering, photography, football(soccer), and cars.

Affiliations/Education

PhD (2024-Present)
Robotics Engineer (2022-2024)
Undergraduate (2018-2022)
Research project (2022)
Associate's of Science (2017-2018)

Research/Projects

Towards Open-World Mobile Manipulation in Homes: Lessons from the Neurips 2023 HomeRobot Open Vocabulary Mobile Manipulation Challenge

Sriram Yenamandra*, Arun Ramachandran*, Mukul Khanna*, Karmesh Yadav*, Jay Vakil*, Andrew Melnik, Michael Büttner, Leon Harz, Lyon Brown, Gora Chand Nandi, Arjun PS, Gaurav Kumar Yadav, Rahul Kala, Robert Haschke, Yang Luo, Jinxin Zhu, Yansen Han, Bingyi Lu, Xuan Gu, Qinyuan Liu, Yaping Zhao, Qiting Ye, Chenxiao Dou, Yansong Chua, Volodymyr Kuzma, Vladyslav Humennyy, Ruslan Partsey, Jonathan Francis, Devendra Singh Chaplot, Gunjan Chhablani, Alexander Clegg, Theophile Gervet, Vidhi Jain, Ram Ramrakhya, Andrew Szot, Austin Wang, Tsung-Yen Yang, Aaron Edsinger, Charlie Kemp, Binit Shah, Zsolt Kira, Dhruv Batra, Roozbeh Mottaghi, Yonatan Bisk, Chris Paxton

In review

Website/ Paper/

Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Open-X X-Embodiment Collaboration

ICRA 2024 (Best conference award)

Website/ Paper/ Dataset/ Code/

OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics

Peiqi Liu*, Yaswanth Orru*, Jay Vakil, Chris Paxton, Nur Muhammad "Mahi" Shafiullah†, Lerrel Pinto†

RSS 2024

Website/ Paper/ Code

RoboHive: A Unified Framework for Robot Learning

Vikash Kumar, Rutav Shah, Gaoyue Zhou, Vincent Moens, Vittorio Caggiano, Jay Vakil, Abhishek Gupta, and Aravind Rajeswaran .

NeurIPS 2023

Website/ Paper/ Dataset/ Code/ PyPI

RoboAgent: Towards Sample Efficient Robot Manipulation with Semantic Augmentations and Action Chunking

Homanga Bharadhwaj*, Jay Vakil*, Mohit Sharma*, Abhinav Gupta, Shubham Tulsiani, and Vikash Kumar.

Accepted at:

Website/ Paper/ Dataset/ Code



Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence?

Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma, Claire Chen, Sneha Silwal, Aryan Jain, Vincent-Pierre Berges, Tingfan Wu, Jay Vakil, Pieter Abbeel, Jitendra Malik, Dhruv Batra, Yixin Lin, Oleksandr Maksymets, Aravind Rajeswaran, Franziska Meier

NeurIPS 2023

Website/ Paper/ Dataset/ Code


Spatial-Language Attention Policies for Efficient Robot Learning

Priyam Parashar, Vidhi Jain, Xiaohan Zhang, Jay Vakil, Sam Powers, and Chris Paxton

CoRL 2023

Website/ Paper


Master Controller For High Energy Electron Source Part II

Jay Vakil*, Esayas Abera*, Cyrus Safi*, Wayne Kimura

Presentation