Alex Podgorny

About Me

I am a PhD student in Statistics at the Institut de Recherche Mathématique Avancée (IRMA), under the supervision of Laurent Gardes. My research focuses on the analysis of high-dimensional conditional extreme quantiles, dimension reduction methods for tail index estimation, and machine learning approaches for rare event modeling.

My CV is available here (PDF).

Research

Summary

My thesis lies in the field of extreme value statistics, with a particular focus on the estimation of conditional extreme quantiles in high dimensions. It is structured around three main contributions: (1) the construction of confidence intervals for extreme quantiles across all domains of attraction, (2) the development of a novel dimension reduction method tailored to conditional tail index estimation, and (3) a comparative study of modern techniques (machine learning and dimension reduction) for conditional extreme quantile estimation.

Publications

• Gardes, L., Maistre, S., and Podgorny, A. (2025). Asymptotic confidence intervals for extreme quantiles in a maximum domain of attraction, Electronic Journal of Statistics, 19(1), 1103–1132. [HAL]
• Gardes, L., and Podgorny, A. (2025). Dimension reduction for the estimation of the conditional tail-index, Scandinavian Journal of Statistics, to appear. [HAL]
• Gardes, L., and Podgorny, A. (2025). Extreme Conditional Quantile Estimation in High Dimensions: A Comparative Study, Preprint. [HAL]

Conferences

• A. Podgorny. Asymptotic confidence interval for extreme quantiles, 13th International Conference on Extreme Value Analysis (EVA 2023), University of Milan, May 2023.
• A. Podgorny. Dimension reduction for conditional tail-index estimation, 55th Journées de Statistique (JdS 2024), University of Bordeaux, May 2024.

Teaching

I taught biostatistics at the University of Strasbourg:

• In second-year undergraduate (L2), from 2022 to 2025
• In third-year undergraduate (L3), from 2022 to 2024