Ajay U. Mandlekar

Picture of Ajay. 

Ajay Mandlekar
Ph.D. Candidate
Stanford Vision and Learning Lab
Department of Electrical Engineering
Stanford University

Advisors: Silvio Savarese and Fei-Fei Li


Email: amandlek@cs.stanford.edu
Twitter: @AjayMandlekar
Google Scholar: Ajay Mandlekar
Github: amandlek
CV: link

Recent News

  • [November 2021] Our large-scale study for learning from offline human demonstrations was presented as an oral (6.5% acceptance) at CoRL 2021! See the talk here.

  • [September 2021] Our work on MOMART, a system for collecting and learning from mobile manipulation demonstrations, and our paper on S4RL, a data augmentation method for offline policy learning, were accepted at CoRL 2021.

  • [August 2021] We released robomimic, a framework for robot learning from demonstration. It offers a broad set of demonstration datasets collected on robot manipulation domains, and learning algorithms to learn from these datasets.

  • [May 2021] Our work on collaborative teleoperation with Multi-Arm RoboTurk was nominated as a best multi-robot systems paper finalist at ICRA 2021!

About Me

I am a PhD candidate in the Stanford Vision and Learning Lab, jointly advised by Silvio Savarese and Fei-Fei Li. My work focuses on developing systems and algorithms to allow robots to leverage human insight for manipulation tasks.