Harshit Sikchi

Harshit Sikchi

  Computer Science @ UT Austin

  hsikchispam[at]utexas.edu


News

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 Interactive Agent Learning: enabling agents 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.

Talks, Teaching and Reviewing

Invited Talks

2023: Gave a talk on my imitation learning work at Facebook Research (FAIR) and Microsoft Research.

RL reading group at UT Austin

Hosting the RL reading group (RLRG) at UT Austin. More details: RLRG Webpage

Reviewing

Serving as a Reviewer for RLC 2024, ICML 2024 Workshop proposals, ICML 2024, ICLR 2024, NeurIPS 2023, ICML 2023, ICLR RRL 2023, ICRA 2023, ICLR 2022, ICML 2022, NeurIPS 2022, CoRL 2022, NeurIPS 2022 Offline RL Workshop.

Organizing

Organizing the RL beyond Rewards workshop at RL Conference 2024 and Workshop on Models of Human Feedback for AI Alignment at ICML 2024

CS394R: Reinforcement Learning: Theory and Practice

Teaching Assistant for Spring 2022. Taught by Prof. Scott Niekum and Prof. Peter Stone