Harshit Sikchi
Researcher at OpenAI
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolHarshit Sikchi is a research scientist at OpenAI with a decade of experience building and researching reinforcement learning and robot learning systems. He holds a PhD from UT Austin and an MS from Carnegie Mellon, and has a track record of internships and research roles across Meta, NVIDIA, ETH Zurich, and industry startups where he tackled unsupervised RL, multi-agent logistics, and fast simulation. His work spans reward learning, safe and model-based RL, and practical motion-planning solutions—skills honed from leading perception and planning efforts at IIT Kharagpur to developing FlowPlan for low-cost trajectory sampling. Notably, he led a scalable, near-real-time multi-agent logistics solver that made NP-hard problems tractable in large fleets, showing a blend of algorithmic rigor and systems engineering. Based in San Francisco, he focuses on getting robots to learn from limited, heterogeneous data sources and to reason under uncertainty. Outside core research, he combines academic depth with product-minded implementations that push RL methods toward real-world deployment.
10 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at The University of Texas at AustinHigher Secondary Education Science, Higher Secondary Education Science at DAV Public school, KotaMasters Computer Science, Masters Computer Science at Carnegie Mellon UniversityBachelor’s Degree Computer Science, Bachelor’s Degree Computer Science at Indian Institute of Technology, Kharagpur
English, Hindi, Marathi, Sanskrit, Marwari
Github Skills (83)
weighted10
actor-critic9
deep-q-network9
q-learning8
deep-reinforcement-learning8
hydra8
stable-baselines8
sac8
gymnasium8
dqn8
ddpg8
multidimensional8
image-processing7
actor7
nonlinear7
Programming languages (5)
Github contributions (5)
hari-sikchi/offline_rl
Aug 2020 - Aug 2022
Contributions:1 release, 22 commits, 8 pushes in 2 years
hari-sikchi/safeRL
Oct 2018 - Sep 2021
Safe Reinforcement Learning algorithms
Contributions:1 release, 51 commits, 41 pushes in 2 years 11 months
multiagent-reinforcement-learningstable-baselinesgymnasiumdeep-reinforcement-learningreinforcement
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