I’m a French postdoctoral researcher interested in both prediction and causation. My research stands at the crossroads of these two worlds.

A lot of causal estimators have been developed, but little guidance exists about when to use (or not) them. The heart of my PhD was to compare the performances of such estimators in various contexts through simulations and how mixing them with machine learning. But causal inference is not only a statistical/estimation problem. Identifiability of causal effects is also a crucial challenge in modern research. Thereby, my current research aims to develop a tool to check positivity in various contexts (, e.g.,, mediation or longitudinal settings) non-parametrically. Machine learning is also a powerful tool for prediction. I’m currently developing a longitudinal predictive score for optimizing dialysis sessions thanks to an IVADO postdoctoral fellowship.

From August, I will be a postdoctoral researcher at Université Laval (Québec), thanks to a CRM-StatLab-CANSSI fellowship.

Interests: Causal inference, Methodology, Prediction, R Programming, Simulation study, Super learning