Zhenbang Wang

Morristown, New Jersey

I am an Associate Statistical Project Leader at Sanofi. I develop causal inference and machine learning methods for clinical trials and observational research, with a focus on heterogeneous treatment effects, causal estimands, and reliable production workflows.

Before my current role, I worked on:

Production-scale causal ML for a one-million-patient observational cohort, including propensity-score methods, generalized random forests, Bayesian shrinkage, and sensitivity analysis.
Statistical methodology for regression with mismatched linked data during my Ph.D. at George Mason University with Prof. Martin Slawski.
Statistical research at Rutgers University and mathematics at Arcadia University.

My broader interests include causal machine learning, data integration, Bayesian modeling, survival analysis, and trustworthy applications of AI in high-stakes settings.

You can find more detail in my CV, publications, software projects, and learning notes. My earlier academic site is archived at George Mason University.

news

Jan 01, 2026	I started a new role as Associate Statistical Project Leader at Sanofi.
Jul 01, 2025	Our paper, “A General Framework for Regression with Mismatched Data Based on Mixture Modelling,” appeared in the Journal of the Royal Statistical Society Series A.
Apr 25, 2023	Our work on regularization for shuffled data was presented at AISTATS 2023.

selected publications

JRSS A

A General Framework for Regression with Mismatched Data Based on Mixture Modelling

Martin Slawski, Brady T. West, Priyanjali Bukke, and 3 more authors

Journal of the Royal Statistical Society Series A: Statistics in Society, 2025

DOI arXiv Bib HTML

@article{slawski2025general,
  title = {A General Framework for Regression with Mismatched Data Based on Mixture Modelling},
  author = {Slawski, Martin and West, Brady T. and Bukke, Priyanjali and Wang, Zhenbang and Diao, Guoqing and Ben-David, Emanuel},
  journal = {Journal of the Royal Statistical Society Series A: Statistics in Society},
  volume = {188},
  number = {3},
  pages = {896--919},
  year = {2025},
  doi = {10.1093/jrsssa/qnae083},
}

AISTATS

Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group

Zhenbang Wang, Emanuel Ben-David, and Martin Slawski

In Proceedings of the 26th International Conference on Artificial Intelligence and Statistics, 2023

Bib HTML PDF

@inproceedings{wang2023regularization,
  title = {Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group},
  author = {Wang, Zhenbang and Ben-David, Emanuel and Slawski, Martin},
  booktitle = {Proceedings of the 26th International Conference on Artificial Intelligence and Statistics},
  series = {Proceedings of Machine Learning Research},
  volume = {206},
  pages = {2939--2959},
  year = {2023},
  publisher = {PMLR},
}

WIREs

Regression with Linked Datasets Subject to Linkage Error

Zhenbang Wang, Emanuel Ben-David, and Martin Slawski

WIREs Computational Statistics, 2022

DOI Bib HTML

@article{wang2022regression,
  title = {Regression with Linked Datasets Subject to Linkage Error},
  author = {Wang, Zhenbang and Ben-David, Emanuel and Slawski, Martin},
  journal = {WIREs Computational Statistics},
  year = {2022},
  doi = {10.1002/wics.1570},
}