Solesne Bourguin

Solesne Bourguin is an Associate Professor in the Department of Mathematics and Statistics at Boston University. She is a member of the Probability and Statistics research group. Her research focuses on advanced topics in stochastic analysis, including stochastic dynamical systems, fractional Brownian motion, Malliavin calculus, Stein's method, and free probability theory. She teaches graduate and undergraduate courses such as Probability Theory II and Linear Algebra.

Her research interests emphasize the theoretical foundations of stochastic processes, with applications to nonlinear statistics and random matrices. Recent work explores quantitative analysis of stochastic iterative algorithms and Gaussian approximations in high-dimensional settings. She has contributed to understanding fluctuation dynamics in multiscale systems driven by fractional Brownian motion and has published in leading journals like the Electronic Journal of Probability and Stochastic Processes and their Applications.

Bourguin's recent publications highlight her expertise in topics like functional Gaussian approximations, moderate deviation principles, and spherical Poisson waves. These studies often combine techniques from Malliavin calculus and Stein's method to derive precise probabilistic estimates. She also investigates the limiting behavior of correlated Wishart matrices in high-dimensional regimes, contributing to random matrix theory.

Scientific awards and grants are not explicitly listed in the provided information. She actively participates in academic activities, including organizing Boston University's Statistics and Probability Seminar Series. Her teaching reflects her commitment to both foundational and advanced mathematical education, spanning topics from linear algebra to stochastic processes.