Hi!

I’m a probabilist interested in rare events and extreme values. I hold PhDs from Université de Lausanne and the Steklov Mathematical Institute in St. Petersburg.

Recently my research has expanded into scientific machine learning: I work on neural-network solvers for mean-field games arising in macroeconomics (HANK models, master equation), in collaboration with the Department of Economics at HEC Lausanne.

Research interests: Extreme value theory, Large deviations, Gaussian random fields, Stochastic analysis, Scientific machine learning.

Recent Highlights

Introduction to Regularity Structures talk

Mini-course (4 lectures) (2026)

Extremes of uncorrelated gamma-reflected Brownian motions with trend publication

Pavel Ievlev, Svyatoslav Novikov

Scandinavian Actuarial Journal (2025)

Extremes of vector-valued locally additive Gaussian fields with application to double crossing probabilities publication

Pavel Ievlev, Nikolai Kriukov

Electronic Journal of Probability (2025)

Extremes of Brownian decision trees publication

Pavel Ievlev, Nikolai Kriukov, Krzysztof Dębicki

under review (2025)

Random eigenvalues of nanotubes publication

Artur Bille, Victor Buchstaber, Pavel Ievlev, Svyatoslav Novikov, Evgeny Spodarev

Journal of Physics A: Mathematical and Theoretical (2025)