Benjamin Fehrmanمشاهده پروفایل
استادیار
Benjamin Fehrman is an Assistant Professor in the Department of Mathematics at Louisiana State University, specializing in stochastic analysis with a focus on stochastic partial differential equations and their applications to statistical physics. His research encompasses diffusion processes in random environments, stochastic homogenization, and randomized optimization algorithms in machine learning. His research interests center on the mathematical theory of stochastic partial differential equations, particularly those arising in statistical physics. Fehrman investigates fluctuating hydrodynamics, non-equilibrium systems, and the connection between interacting particle systems and their continuum limits. His work often involves developing well-posedness theory for challenging SPDEs with conservative noise structures and analyzing large-scale behavior in random media. Analysis of his recent publications reveals a strong focus on conservative stochastic PDEs and their connection to interacting particle systems, particularly the zero-range process and symmetric simple exclusion process. His research shows increasing attention to large deviation principles, kinetic formulations of skeleton equations, and the mathematical foundations of fluctuating hydrodynamics. The interdisciplinary nature of his work bridges probability theory, partial differential equations, and mathematical physics. Fehrman's research has been supported by prestigious grants including the National Science Foundation DMS-Probability Standard Grant 2348650, the Simons Foundation Travel Grant MPS-TSM-00007753, and the Louisiana Board of Regents RCS Grant 20130014386. He has supervised PhD students Andrea Clini (University of Oxford, 2020-2024) and Shyam Popat (University of Oxford, 2021-present), as well as postdoc Simone Floreani (University of Oxford, 2022-2023). Fehrman has also organized significant academic events including the "Interacting Particles, Fluctuating Systems, and SPDEs" workshop at the University of Oxford in June 2023, funded by an EPSRC Early Career Fellowship. His teaching portfolio includes advanced courses in stochastic analysis, stochastic differential equations, and stochastic homogenization at both Louisiana State University and the University of Oxford, where he previously held a position.
