Michele Ceriotti

EPFL STI IMX COSMO
MXG 337 (Bâtiment MXG)
Station 12
1015 Lausanne

Mission

Development and application of statistical sampling and machine-learning algorithms to achieve predictive atomic-scale modelling of molecules and materials, and to understand structure-property relations.
Michele Ceriotti received his Ph.D. in Physics from ETH Zürich. He spent three years in Oxford as a Junior Research Fellow at Merton College. Since 2013 he leads the laboratory for Computational Science and Modeling, in the institute of Materials at EPFL, that focuses on method development for atomistic materials modeling based on statistical mechanics and machine learning. He is one of the core developers of several open-source software packages, including metatensor.org, ipi-code.org and chemiscope.org, and proudly serves the atomistic modeling community as an associate editor of the Journal of Chemical Physics, as a moderator of the physics.chem-ph section of the arXiv, and as an editorial board member of Physical Review Materials.

Awards

Volker Heine Young Investigator Award

2013

ERC Starting Grant

European Research Council

2016

IUPAP-C10 Young Scientist Prize

IUPAP

2018

ERC Consolidator Grant

European Research Council

2021

Fellow of the European Lab for Learning and Intelligent Systems (ELLIS)

ELLIS

2023

E. Bright Wilson Prize

Department of Chemistry, Harvard University

2024

Research

Current Research Fields

Atomistic computer simulations, statistical mechanics, machine learning, molecular dynamics, nuclear quantum effects, aqueous systems, molecular materials, high-entropy materials.