Harshit Sikchi
Computer Science @ UT Austin
hsikchi[at]utexas.edu
News
- 05/01/2023: I'll be starting as a research intern at Meta AI research working on RL.
- 02/16/2023: Our recent work on Dual RL is now public. Check it our for SOTA algos in RL and IL .
- 01/09/2023: rank-game (Unified approach to learning from preferences and imitations) was featured in the Microsoft Research Blog.
- 10/23/2022: Our work FlowPlan awarded best paper at IROS BADUE 2022.
- 03/10/2022: I'll be starting as a research intern at NVIDIA research working on reinforcement learning.
- 11/07/2021: Our work on model-based RL LOOP nominated for Best Paper at CoRL 2021.
About
I am a PhD student in the Computer Science Department at UT Austin co-advised by Prof. Scott Niekum and Prof. Amy Zhang . I am interested in pushing the limits of Robot Learning: enabling robots to make the most of limited data and make sense of different sources of information present in the world to improve their ability. I am broadly interested in Reinforcement Learning (Theory and Practice) to achieve this goal.Previously, I was a Master’s student in Computer Science (2019-20) at the School of Computer Science, Carnegie Mellon University where I worked at Robot Perceiving and Doing lab advised by Prof. David Held. In the summer of 2020, I worked on Imitative Motion Planning at Uber ATG . I worked on Reinforcement Learning for large action spaces during my prior internship at NVIDIA and spent some time at ETH Zurich working on Semantic Segmentation. Prior to this, I received my Bachelor’s degree from the Department of Computer Science at the Indian Institute of Technology, Kharagpur. My studies at IIT Kharagpur were supported by the Aditya Birla Scholarship (2015-19). I spent most of time at IIT Kharagpur working on Autonomous cars at the Autonomous Ground Vehicle Lab under the supervision of Professor Debashis Chakravarty. I led the perception and planning effort-working on Lane Detection, Frenet Planner, Hybrid A* Planner, and Segmentation. I completed my bachelor thesis on Safe Reinforcement Learning with Prof. Pabitra Mitra. In my spare time, I enjoy playing tennis, badminton, skiing, running, hiking, and traveling.