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@stanford.edu
Twitter: @AjayMandlekar

Recent News

  • [December 2020] We recently extended RoboTurk to enable human-in-the-loop teleoperation and developed Intervention Weighted Regression, a simple and effective algorithm to learn from such interventions.

  • [December 2020] We recently extended RoboTurk to enable multi-user collaborative teleoperation on challenging multi-arm tasks. We collected datasets on novel two-arm and three-arm tasks and developed a residual policy framework to address the problem of learning from multi-user demonstration data.

  • [December 2020] Check out our preprint on Deep Affordance Foresight, a new model that extends the classical definition of affordance to enable long-horizon planning.

  • [September 2020] We released robosuite v1.0, a modular simulation framework and benchmark for robot learning.

About Me

I am a PhD candidate in the Stanford Vision and Learning Lab advised by Silvio Savarese and Fei-Fei Li. I work on applying Reinforcement Learning and Imitation Learning to Robotics. In particular, I'm interested in building systems and algorithms to allow robots to leverage human insight for manipulation.