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 http://www.ma.ic.ac.uk/~pavl
Pavliotis G, Girolami M, Gaskin T, 2023, Neural parameter calibration for large-scale multi-agent models, Proceedings of the National Academy of Sciences (pnas)
Pavliotis GA, Zanoni A, 2022, Eigenfunction Martingale Estimators for Interacting Particle Systems and Their Mean Field Limit, Siam Journal on Applied Dynamical Systems, Vol:21, Pages:2338-2370
Abdulle A, Pavliotis GA, Zanoni A, 2022, Eigenfunction martingale estimating functions and filtered data for drift estimation of discretely observed multiscale diffusions, Statistics and Computing, Vol:32, ISSN:0960-3174, Pages:1-33
et al., 2022, Geometric methods for sampling, optimization, inference, and adaptive agents, Vol:46, ISSN:0169-7161, Pages:21-78
Pavliotis GA, Stuart AM, Vaes U, 2022, Derivative-free Bayesian inversion using multiscale dynamics, Siam Journal on Applied Dynamical Systems, Vol:21, ISSN:1536-0040, Pages:284-326