Ajay U. Mandlekar
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Ajay Mandlekar |
Contact
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.
[July 2020] We are organizing the Advances and Challenges in Imitation Learning for Robotics workshop at RSS 2020.
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.
Education
Ph.D. (in progress), Electrical Engineering, Stanford University, September 2016 - Present
M.S., Computer Science, Stanford University, June 2018
B.S., Electrical Engineering, California Institute of Technology, June 2016
B.S., Computer Science, California Institute of Technology, June 2016
Monta Vista High School, Class of 2012