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 develop algorithms for robots to learn new skills from minimal supervision, search to creatively solve complex problems and continually improve with self-practice. This requires strategic robot learning to decide what to learn—focusing on the right policies and models—and how to learn—combining strategies like imitation learning, reinforcement learning and search to solve tasks resource-efficiently. 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, especially if you are a student at Brown or MIT. 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

Email / Google Scholar / LinkedIn

news

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.
Jul 28, 2024	Invited talks at IISc and IIT Madras.
May 23, 2024	I defended my thesis on Plan to Learn: Active Robot Learning by Planning (video)

selected publications

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 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},
}

SCALE: Causal Learning and Discovery of Robot Manipulation Skills using Simulation

Tabitha Edith* Lee*, Shivam Vats*, Siddharth Girdhar, and Oliver Kroemer

In 7th Annual Conference on Robot Learning (CoRL), 2023

Bib PDF

@inproceedings{lee2023scale,
  title = {SCALE: Causal Learning and Discovery of Robot Manipulation Skills using Simulation},
  author = {Lee*, Tabitha Edith* and Vats*, Shivam and Girdhar, Siddharth and Kroemer, Oliver},
  booktitle = { 7th Annual Conference on Robot Learning (CoRL)},
  year = {2023},
  video = {https://www.youtube.com/watch?v=kxMdc8aH564},
}

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.},
}