🌟 I'm on the faculty job market in Spring 2018! 🌟

I am a Postdoctoral Researcher at Stanford working with Fei-Fei Li and Silvio Savarese at Stanford AI Lab. I also collaborate closely with Marco Pavone and his group.

My current research focuses on machine learning algorithms for perception and control in robotics. I am specifically interested in enabling efficient imitation in robot learning and human-robot interaction.

I received MS in Computer Science and Ph.D. in Operations Research from the UC, Berkeley in 2016. I was advised by Ken Goldberg in the Automation Lab as a part of the Berkeley AI Research Lab (BAIR). I also worked closely with Pieter Abbeel, Alper Atamturk and UCSF Radiation Oncology.

Research Interests: Machine Learning, Optimization, Design in Robotics & Healthcare.

Contact me: garg@cs·stanford·edu
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Recent News

  • 18 Feb 2018:

    3 Papers accepted at CVPR, ICRA and WACV 2018 👍

  • 02 Oct 2017:

    Organizing Stanford Robotics Seminar Series 🎙️

  • 25 Sep 2017:

    Co-Teaching CS 332 Advanced RL 📕

  • 01 Sep 2017:

    4 Papers accepted at ISRR, CoRL and 3DV, 2017 👍

  • 01 Jul 2017:

    CoRL and ISRR papers Submitted

Recent Research

Rethinking Generalization in Robot Learning
At Stanford, I am leading the effort in Rethinking Generalization in Robot Learning. It is a multi-proged effort in developing hierarcical Deep RL abstractions along with learning from video demonstrations. Read More
Learning & Automation in Surgical Subtasks
We are working towards surgical sub-task automation and exploring a data driven approach for reduction in training effort with unsupervised task structure learning. Read More
Brachytherapy for Cancer: Planning and Delivery
Brachytherapy is an internal form of radiotherapy for cancer, involving radioactive source placement in proximity of the tumor. We have worked on novel patient specific delivery methods for interstitial (e.g. prostate) and intracavitary (e.g. oral/thoracic, GYN) tumors. Read More

Coverage in Media/Press

  • IEEE Spectrum
  • IEEE Spectrum
  • IEEE Spectrum
  • New York Times
  • Med Gadget
  • 3D Printing World
  • Phys.Org

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