Imperial College London

Professor Grigorios A. Pavliotis

Faculty of Natural SciencesDepartment of Mathematics

Professor of Applied Mathematics
 
 
 
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Contact

 

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

 
 
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Location

 

736aHuxley BuildingSouth Kensington Campus

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Summary

 

Summary

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

Publications

Journals

Gaskin T, Pavliotis GA, Girolami M, 2023, Neural parameter calibration for large-scale multiagent models, Proceedings of the National Academy of Sciences, Vol:120, ISSN:0027-8424

Zagli N, Pavliotis GA, Lucarini V, et al., 2023, Dimension reduction of noisy interacting systems, Physical Review Research, Vol:5

Abdulle A, Garegnani G, Pavliotis GA, et al., 2023, Drift estimation of multiscale diffusions based on filtered data, Foundations of Computational Mathematics, Vol:23, ISSN:1615-3375, Pages:33-84

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

Barp A, Da Costa L, França G, et al., 2022, Geometric methods for sampling, optimization, inference, and adaptive agents, Handbook of Statistics, Vol:46, ISSN:0169-7161, Pages:21-78

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