Nishanth Kumar
AI Research Scientist at Meta
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolNishanth Kumar is a PhD student researcher at MIT CSAIL focused on AI, ML, and robotics, with over a decade of experience bridging research and engineering. He has interned at leading labs including Meta FAIR, NVIDIA, and The AI Institute, contributing to VLM planning, autonomous self-improvement for agents, and robot manipulation systems that combine vision-language models with planning. His work spans publishing and practical system-building—examples include contributions to PGMax and CoRL-accepted active learning research—and emphasizes test-time search and scalable planning for embodied agents. Based in Cambridge, MA, he pairs rigorous academic training (PhD/MS at MIT; BS from Brown) with hands-on product-oriented research experience. A less obvious strength is his early teaching and program-development background, which informs clear communication of complex ideas across research and engineering teams.
11 years of coding experience
1 year of employment as a software developer
Doctor of Philosophy - PhD, AI/ML/Robotics, Doctor of Philosophy - PhD, AI/ML/Robotics at Massachusetts Institute of TechnologyBachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at Brown UniversityHigh School, International Baccalaureate Diploma Programme, High School, International Baccalaureate Diploma Programme at The Indian Public School
English, Tamil, French
Stackoverflow
87reputation
8kreached
0answers
3questions
Github Skills (55)
laravel10
mdp9
jekyll9
python8
agent8
parameterized8
reinforcement-learning8
jekyll-theme8
belief-propagation8
github-pages8
backend7
ros7
xla7
unity-game-engine6
jax6
Programming languages (11)
Github contributions (5)
NishanthJKumar/NishanthJKumar.github.io
Feb 2020 - May 2026
GitHub repo for my personal website: https://nishanthjkumar.com
Contributions:13 PRs, 192 pushes, 14 branches in 6 years 3 months
h2r/parameterized-imitation-learning
Jul 2019 - Apr 2020
Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control
Contributions:44 commits, 11 pushes, 1 branch in 9 months
deep-learningpytorchparameterizedimitation-learning
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