Phd. Student on extreme and unsupervised learning.
I am currently a Wissenschaftlicher Mitarbeiter at Ruhr-Universität Bochum working in the team of Axel Bücher. Prior to this, I completed my PhD in Probability and Statistics at the Jean-Alexandre Dieudonné Laboratory of Université Côte d’Azur, working with the Lemon team at INRIA, Montpellier. My research interests focus on extreme value theory and machine learning.
[4] Alexis Boulin, Elena Di Bernardino, Thomas Laloë, Gwladys Toulemonde, Identifying regions of concomitant compound precipitation and wind speed extremes over Europe,Journal of the Royal Statistical Society Series C: Applied Statistics, Volume 74, Issue 4, November 2025, Pages 1057–1076. [paper]
[3] Alexis Boulin, Elena Di Bernardino, Thomas Laloë, Gwladys Toulemonde, High-Dimensional Variable Clustering based on Maxima of a Weakly Dependent Random Process, Journal of the American Statistical Association, 120(551), 1933–1944. [paper]
[2] Alexis Boulin. 2023. “A Python Package for Sampling from Copulae: Clayton.” Computo, January. [paper]
[1] Alexis Boulin, Elena Di Bernardino, Thomas Laloë, Gwladys Toulemonde, Non-parametric estimator of a multivariate madogram for missing-data and extreme value framework, Journal of Multivariate Analysis, Volume 192, November 2022. [paper]
[1] Alexis Boulin, Estimating Max-Stable Random Vectors with Discrete Spectral Measure using Model-Based Clustering. [ArXiv]
[2] Alexis Boulin, Axel Bücher, Structured linear factor models for tail dependence. [ArXiv]
[3] Alexis Boulin, Erik Haufs, Extrapolating into the Extremes with Minimum Distance Estimation. [ArXiv]
[4] Alexis Boulin, Axel Bücher, Dimension Reduction in Multivariate Extremes via Latent Linear Factor Models. [ArXiv]
You can view my thesis by clicking the link and slides (in french) are also available.