Sumantrak Mukherjee

I work on multi-armed bandits, uncertainty quantification, and sample-efficient decision-making under limited feedback.

I am currently a Junior Researcher at DFKI in the Data Science and its Applications group, where I work under Prof. Sebastian Vollmer. I graduated from BITS Pilani in 2023 with a degree in Electronics and Instrumentation Engineering. Outside research, I like watching and discussing movies, travelling, and cooking new dishes when I am not too tired. I also keep a quiet acknowledgments page for people who have been especially kind to me.

For a more detailed account of my research, see the research page.

Multi-Armed Bandits and Uncertainty Quantification

Sequential decision-making with better priors, transfer, and calibrated uncertainty.

Causal Structure for Efficient Learning

Causal discovery and causal structure leveraged for sample efficiency and transfer.

Spatio-Temporal Event Modeling

Interpretable point processes, benchmarks, and counterfactual event data.

selected publications

bandits + uq

Distributionally Robust Warm Start for a Population of Bandits

Sumantrak Mukherjee, Debabrota Basu, Jasmin Brandt, and 3 more authors

In European Workshop on Reinforcement Learning, 2026

Bib Paper

@inproceedings{mukherjee2026robustwarmstart,
  title = {Distributionally Robust Warm Start for a Population of Bandits},
  author = {Mukherjee, Sumantrak and Basu, Debabrota and Brandt, Jasmin and Bengs, Viktor and H{\"u}llermeier, Eyke and Vollmer, Sebastian Josef},
  booktitle = {European Workshop on Reinforcement Learning},
  year = {2026},
}

bandits + uq

Co-Exploration and Co-Exploitation via Shared Structure in Multi-Task Bandits

Sumantrak Mukherjee, Serafima Lebedeva, Jasmin Brandt, and 7 more authors

In European Workshop on Reinforcement Learning, 2026

Bib Paper

@inproceedings{mukherjee2026multitaskbandits,
  title = {Co-Exploration and Co-Exploitation via Shared Structure in Multi-Task Bandits},
  author = {Mukherjee, Sumantrak and Lebedeva, Serafima and Brandt, Jasmin and Margraf, Valentin and Hanselle, Jonas and Yamaoka, Kanta and Bengs, Viktor and Konigorski, Stefan and H{\"u}llermeier, Eyke and Vollmer, Sebastian Josef},
  booktitle = {European Workshop on Reinforcement Learning},
  year = {2026},
}

event modeling

Neural Spatiotemporal Point Processes: Trends and Challenges

Sumantrak Mukherjee, Mouad Elhamdi, George Mohler, and 4 more authors

Transactions on Machine Learning Research, 2025

Bib Paper

@article{mukherjee2025nstpp,
  title = {Neural Spatiotemporal Point Processes: Trends and Challenges},
  author = {Mukherjee, Sumantrak and Elhamdi, Mouad and Mohler, George and Selby, David A. and Xie, Yao and Vollmer, Sebastian and Gro{\ss}mann, Gerrit},
  journal = {Transactions on Machine Learning Research},
  year = {2025},
}

adjacent interests

X-Hacking: The Threat of Misguided AutoML

Rahul Sharma, Sumantrak Mukherjee, Andrea Sipka, and 4 more authors

In International Conference on Machine Learning, 2025

Bib Paper

@inproceedings{sharma2025xhacking,
  title = {X-Hacking: The Threat of Misguided AutoML},
  author = {Sharma, Rahul and Mukherjee, Sumantrak and Sipka, Andrea and H{\"u}llermeier, Eyke and Vollmer, Sebastian Josef and Redyuk, Sergey and Selby, David A.},
  booktitle = {International Conference on Machine Learning},
  year = {2025},
}

causal learning bandits + uq

Graph Agnostic Causal Bayesian Optimisation

Sumantrak Mukherjee^*, Mengyan Zhang^*, Seth Flaxman, and 1 more author

* joint first authors

In NeurIPS BDU Workshop, 2024

Bib Paper

@inproceedings{mukherjee2024gacbo,
  title = {Graph Agnostic Causal Bayesian Optimisation},
  author = {Mukherjee, Sumantrak and Zhang, Mengyan and Flaxman, Seth and Vollmer, Sebastian},
  booktitle = {NeurIPS BDU Workshop},
  year = {2024},
  author_note = {* joint first authors},
}

news

Oct 04, 2026	I am attending the European Workshop on Reinforcement Learning (EWRL) in Lille and visiting Prof. Debabrota Basu. 🇫🇷
Jul 11, 2026	Distributionally Robust Warm Start for a Population of Bandits is accepted to the European Workshop on Reinforcement Learning. 🎉
Jul 11, 2026	Co-Exploration and Co-Exploitation via Shared Structure in Multi-Task Bandits is accepted to the European Workshop on Reinforcement Learning. 🎉
Jun 26, 2026	We came 3rd in the MLSS Hackathon. 🥉
May 31, 2026	Linear-LLM-SCM: Benchmarking LLMs for Coefficient Elicitation in Linear-Gaussian Causal Models is accepted to the Structured Data 4 Health Workshop at ICML. 🎉
Apr 30, 2026	I am attending the Machine Learning Summer School in New York City from Jun 15 to Jun 26, with a 16.67% acceptance rate. 🗽
Apr 16, 2026	I am attending the Reinforcement Learning Summer School in Milan from June 3 to June 12, with a 32.5% acceptance rate. 🍹
Dec 06, 2025	Presented CLAM: Causal Spatial Disaggregation to Infer Local Effects From Coarse Data at the NeurIPS 2025 CauScien workshop.
Oct 13, 2025	Attended the GEMINI Summer School on addressing the gender data gap in medicine and the application of N-of-1 trials, October 13-17, 2025.
Nov 05, 2024	Released the preprint Graph Agnostic Causal Bayesian Optimisation.
May 23, 2024	Visited Saarbrucken for the workshop on Safe and Causally Informed Deep RL on May 23-24, 2024.