Shivam Vats

I am a postdoc at Brown University, where I work with Prof. George Konidaris on lifelong learning and planning. I also closely collaborate with the Computational Cognitive Science lab at MIT. My current focus is on developing provably resource-rational intelligence that learns strategically to continually improve its planning capabilities for long-term autonomy in complex real-world environments. This ASME article provides a good overview of my work on collaborative factory robots that plan what to learn.

I earned my PhD from the Robotics Institute at CMU where I was co-advised by Prof. Maxim Likhachev and Prof. Oliver Kroemer. 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 closely involved in SymEngine for many years. I also actively 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

🌟 I am on the job market for tenure-track faculty roles in robotics and AI.🌟

Email / Google Scholar / LinkedIn

news

Oct 14, 2025	Honored to be selected as a Rising Star by the 2025 Northeast Robotics Colloquium (NERC).
Aug 12, 2025	Released code for Cost-Optimal Interactive Learning (COIL).
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.

selected publications

RecoveryChaining: Learning Local Recovery Policies for Robust Manipulation

Shivam Vats, Devesh K Jha, Maxim Likhachev, Oliver Kroemer, and Diego Romeres

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2025

Bib PDF Code

@article{vats2025recoverychaining,
  title = {RecoveryChaining: Learning Local Recovery Policies for Robust Manipulation},
  author = {Vats, Shivam and Jha, Devesh K and Likhachev, Maxim and Kroemer, Oliver and Romeres, Diego},
  journal = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year = {2025},
}

Optimal Interactive Learning on the Job via Facility Location Planning

Shivam Vats*, Michelle Zhao*, Patrick Callaghan, Mingxi Jia, Maxim Likhachev, Oliver Kroemer, and George Konidaris

Robotics: Science and Systems (RSS), 2025

Bib PDF Code Website

@article{vats2025coil,
  title = {Optimal Interactive Learning on the Job via Facility Location
           Planning},
  author = {Vats*, Shivam and Zhao*, Michelle and Callaghan, Patrick and Jia, Mingxi and Likhachev, Maxim and Kroemer, Oliver and Konidaris, George},
  journal = {Robotics: Science and Systems (RSS)},
  year = {2025},
}

Multi-Robot Motion Planning with Diffusion Models

Yorai Shaoul*, Itamar Mishani*, Shivam Vats*, Jiaoyang Li, and Maxim Likhachev

13th International Conference on Learning Representations (ICLR), 2025

Bib PDF Code Website 🏆 Spotlight presentation

@article{shaoul2024multi,
  title = {Multi-Robot Motion Planning with Diffusion Models},
  author = {Shaoul*, Yorai and Mishani*, Itamar and Vats*, Shivam and Li, Jiaoyang and Likhachev, Maxim},
  journal = {13th International Conference on Learning Representations (ICLR)},
  year = {2025},
}

Efficient Recovery Learning using Model Predictive Meta-Reasoning

Shivam Vats, Maxim Likhachev, and Oliver Kroemer

In 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023

Bib PDF Code Website

@inproceedings{vats2023efficient,
  title = {Efficient Recovery Learning using Model Predictive Meta-Reasoning},
  author = {Vats, Shivam and Likhachev, Maxim and Kroemer, Oliver},
  booktitle = {2023 IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {7258--7264},
  year = {2023},
  organization = {IEEE},
}

Synergistic scheduling of learning and allocation of tasks in human-robot teams

Shivam Vats, Oliver Kroemer, and Maxim Likhachev

In 2022 International Conference on Robotics and Automation (ICRA), 2022

Bib PDF 🏆 Outstanding Interaction Paper Finalist

@inproceedings{vats2022synergistic,
  title = {Synergistic scheduling of learning and allocation of tasks in human-robot teams},
  author = {Vats, Shivam and Kroemer, Oliver and Likhachev, Maxim},
  booktitle = {2022 International Conference on Robotics and Automation (ICRA)},
  pages = {2789--2795},
  year = {2022},
  organization = {IEEE},
}

SymPy: symbolic computing in Python

Aaron Meurer, and others

PeerJ Computer Science, 2017

Bib PDF

@article{meurer2017sympy,
  title = {SymPy: symbolic computing in Python},
  author = {Meurer, Aaron and others},
  journal = {PeerJ Computer Science},
  volume = {3},
  pages = {e103},
  year = {2017},
  publisher = {PeerJ Inc.},
}