I am a PhD student in MIT EECS, within CSAIL's Learning and Intelligent Systems group. In May 2018, I received an MS in EECS from MIT. In May 2016, I received a BS in EECS, with Highest Honors, from UC Berkeley.
I work in the field of artificial intelligence for robotics. My current interests are in probabilistic inference, planning, and machine learning for human-robot interactive settings involving partial observability. I am also interested in methods for integrating symbolic and geometric reasoning, and have previously worked at the intersection of task and motion planning (TAMP) and reinforcement learning. Please check out my publications if you would like to learn more.
I have enjoyed being a Teaching Assistant numerous times throughout my academic career, and hope to continue in the future.
In Summer 2019, I did a research internship with Abhinav Gupta at Facebook AI Research, in the new Pittsburgh office for robotics. I worked on formulations of intrinsic motivation for learning synergistic behavior via deep reinforcement learning. We were able to get robots to perform bimanual manipulation tasks both in simulation and on real Sawyer arms.
My paper "Integrating Human-Provided Information Into Belief State Representation Using Dynamic Factorization" won Best Paper Award at the 2018 International Workshop on Statistical Relational AI.
In Summer 2017, I did a research internship with Sergey Levine at Google Brain Robotics, working on methods for improving exploration in deep reinforcement learning.
In Summer 2016, I interned as a software engineer at Airbnb, doing machine learning with the Search Ranking team.
In January 2016, I was selected as one of 40 Finalists for the Hertz Fellowship, a highly reputable fellowship for student researchers in the physical, biological, and engineering sciences.
In December 2015, I was selected as the Runner-up for the 2016 Computing Research Association (CRA) Outstanding Undergraduate Researcher Award (Male, PhD-granting institution).