Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Professor of Applied Mathematics



+44 (0)20 7594 8564g.pavliotis Website




621Huxley BuildingSouth Kensington Campus





Grigorios A. Pavliotis is Professor of Applied Mathematics at the Department of Mathematics at Imperial College. His main research interests lie in the areas of stochastic differential equations and diffusion processes, nonequilibrium statistical mechanics and homogenization theory for partial differential equations and stochastic differential equations. He is particularly interested in the development of analytical, computational and statistical techniques for multiscale stochastic systems, in time-dependent statistical mechanics and kinetic theory and in the analysis and development of sampling techniques in high dimensions. Current research projects include inference and control for multiscale systems, the development of computational techniques for calculating transport coefficients, homogenization for multiscale diffusion processes and sampling techniques in molecular dynamics.

His personal webpage can be found at



Abdulle A, Pavliotis GA, Vaes U, Specral methods for multiscale stochastic differential equations, Siam/asa Journal on Uncertainty Quantification, ISSN:2166-2525

Gomes SN, Kalliadasis S, Papageorgiou DT, et al., 2017, Controlling roughening processes in the stochastic Kuramoto-Sivashinsky equation, Physica D-nonlinear Phenomena, Vol:348, ISSN:0167-2789, Pages:33-43

Tomlin RJ, Papageorgiou DT, Pavliotis GA, et al., 2017, Three-dimensional wave evolution on electrified falling films, Journal of Fluid Mechanics, Vol:822, ISSN:0022-1120, Pages:54-79

Bonnaillie-Noel V, Carrillo JA, Goudon T, et al., 2016, Efficient numerical calculation of drift and diffusion coefficients in the diffusion approximation of kinetic equations, Ima Journal of Numerical Analysis, Vol:36, ISSN:0272-4979, Pages:1536-1569

Duncan AB, Lelievre T, Pavliotis GA, et al., 2016, Variance Reduction Using Nonreversible Langevin Samplers, Journal of Statistical Physics, Vol:163, ISSN:0022-4715, Pages:457-491

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