I develop theory and algorithms in statistical machine learning for decision-making and inference with flexible models. My work identifies which estimation errors and sampling effects matter for the question being asked—and how to control them without demanding more accuracy or stability than necessary. This guides my research on nuisance-robust inference, adaptive experiments, structured outcomes, and policy learning.

I am particularly interested in applying these ideas to biology and biomedicine.

About Me

I am a Research Fellow at the Gatsby Computational Neuroscience Unit at University College London, where I work with Arthur Gretton.

Before joining UCL, I was a postdoctoral researcher in the MIND team at Inria, where I worked on nuisance-robust causal inference and mediation analysis for biomedical applications. I completed my PhD jointly with Inria Thoth and the Criteo AI Lab, focusing on offline policy learning and sequential learning. Earlier, at the Institute for Infocomm Research, I worked on deep generative models, anomaly detection, and medical imaging.

CV · PhD thesis

Feel free to reach out if you wish to collaborate, exchange ideas, or seek Master's thesis supervision. Contact: (first initial).(last name) [at] ucl.ac.uk.

News

• June 2026: Organized the Advances on Adaptive Experimentation (AAE) Workshop at the Gatsby Unit, UCL.
• June 2026: Our paper Fast Best-in-Class Regret for Contextual Bandits was accepted at UAI 2026.

Selected Publications

• Efficient Inference after Directionally Stable Adaptive Experiments
  Z. Shen*, H. Zenati*, N. Kallus, A. Gretton, K. Khamaru, A. Bibaut.
  Preprint, 2026.
  [arXiv]

• Kernel Treatment Effects from Adaptively Collected Data
  Houssam Zenati, Bariscan Bozkurt, Arthur Gretton.
  AISTATS, 2026.
  [Paper] · [Code]

• Semiparametric Efficient Test for Interpretable Distributional Treatment Effects
  Houssam Zenati, Arthur Gretton.
  Preprint, 2026.
  [Paper]

• Fast Best-in-Class Regret for Contextual Bandits
  Girard, Samuel, Nathan Kallus, Jill-Jênn Vie, Arthur Gretton, Aurélien Bibaut, and Houssam Zenati.
  UAI, 2026.
  [arXiv]

• Sequential Counterfactual Risk Minimization
  Houssam Zenati, Eustache Diemert, Matthieu Martin, Julien Mairal, Pierre Gaillard.
  ICML, 2023.
  [Paper] · [Code]

© Copyright 2026 Houssam Zenati. Last updated: September, 2026.