Shivam Vats

I am a Postdoctoral Research Associate at the Intelligent Robot Lab led by Prof. George Konidaris in the Department of Computer Science, Brown University. I earned my PhD from the Robotics Institute at CMU where I was co-advised by Prof. Maxim Likhachev and Prof. Oliver Kroemer. I work on integrating learning and planning to build intelligent robots that learn and generalize resource-rationally. I develop planning algorithms that learn from experience and active learning algorithms that strategically decide what and how to learn to improve planning. This ASME article provides a good overview of my work on collaborative robots that plan what to learn.
Previously, I studied maths and computing at Indian Institute of Technology (IIT) Kharagpur where I worked with Prof. P.P. Chakrabarti and Prof. Bibhas Adhikari on heuristic search. I was a core developer of SymPy and an active contributor to SymEngine for many years. I also regularly participated in the Intelligent Ground Vehicle Competition as a member of the Autonomous Ground Vehicle Group.
I am looking for new collaborations and am always happy to chat about robotics and research. Do reach out if you are interested in working with me. Here are some of my ongoing projects:
- learning and planning with particle-based world models
- learning composable manipulation skills from videos
- multi-task interactive learning from human feedback
🌟 Submit your work to our workshop on Resource-Rational Robot Learning at CoRL 2025. 🌟
news
Aug 12, 2025 | Released code for Cost-Optimal Interactive Learning (COIL). |
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Aug 8, 2025 | We are organizing a workshop on Resource-Rational Robot Learning at CoRL 2025. See you in Seoul! |
Jun 15, 2025 | RecoveryChaining: Learning Local Recovery Policies for Robust Manipulation has been accepted to IROS 2025. |
May 25, 2025 | Our paper on Optimal Interactive Learning on the Job via Facility Location Planning has been accepted to RSS 2025. |
Mar 1, 2025 | Our paper on Multi-Robot Motion Planning with Diffusion Models was selected for Spotlight presentation at ICLR. |