USC (PhD student in Robotics)
5+ years work experience (mostly algorithmic robotics)
Georgia Tech (MS Comp Sci, Robotics)
UT Austin (MS Mech Engg, Controls)
IIT Bombay (Mech Engg)
I am a computer science Ph.D. student in robotics & machine learning at the University of Southern California (USC), advised by Gaurav Sukhatme. Broadly, I work on combining planning algorithms with learning to achieve greater autonomy for robots, with experience in object manipulation, control theory, and deep reinforcement learning.
Jan 2022: I have accepted an internship at Amazon Robotics this summer.
May 2021: Chaired ICRA 2021 session on "Field Robotics: Control"
Mar 2021: Our paper on adaptive sampling with POMDPs for environmental monitoring has been accepted to ICRA 2021! (PDF)
Feb 2021: Our paper on planning for large-scale exploration in the real world has been accepted to ICAPS 2021! This is part of an ongoing collaboration with NASA JPL and Caltech for the SubT challenge. (PDF).
Aug 2020: Our paper on using robots for programming education has been accepted at the American Society of Engineering Education (ASEE) Annual Conference! This was the outcome of volunteering with USC VAST to teach children and elementary school teachers programming using robots. (PDF).
Fall 2019: Designed and TA'ed a new robotics course for Masters' students (Website).
Summer 2019: I did a summer internship at Bosch Research in Sunnyvale.
Jan 2019: Our proposal for the Amazon Research Awards was accepted! This was work with Ryan Julian to learn embeddings for tasks, so as to create composable motiions for a robot. See more details here.
Fall 2018: I joined USC for a PhD in robotics!
2016-2018: I worked in Symbotic LLC, focussing on robot manipulation.