Biography

2007-2010: Ph.D. student in Physics at ETHZ (Prof. Michele Parrinello)

After a M.Sc. in Materials Science at the University of Milano-Bicocca, Michele Ceriotti joined the group of Michele Parrinello in Lugano, where he developed algorithms to improve several aspects of molecular dynamics simulations. These included linear-scaling electronic structure methods to simulate larger systems, a novel framework to use correlated-noise Langevin dynamics to manipulate with exquisite precision the sampling properties of molecular dynamics, and a non-linear dimensionality reduction method to describe in a coarse-grained manner the configuration space of structurally complex materials.

2011- 2013: Post-doctoral researcher at the University of Oxford (Junior Research Fellow at Merton College; Marie Curie IEF, Newton International Fellowship, SNF fellowship, Prof. David Manolopoulos)

After graduating, he moved to Oxford. After a brief collaboration with Andrea Cavalleri and Nicola Marzari, he joined the group of David Manolopoulos in the department of Theoretical Chemistry. He combined path integral molecular dynamics and correlated-noise generalized Langevin equations to dramatically reduce the computational burden associated with the modeling of the quantum properties of light nuclei. These enhanced methods made it possible to understand some features of the behavior of water, including quantum fluctuations of the hydrogen bond, isotope effects on the melting of water,and isotope fractionation at the water-vapor interface.

Nov. 2013 - Present: Tenure-track Assistant Professor in the Institute of Materials Science at the École Polytechnique Fédérale de Lausanne.

In autumn 2013 Michele Ceriotti joined the department of Materials Science at EPFL, establishing the Laboratory of Computational Science and Modeling (COSMO). His research spans different classes of compounds, including hydrogen-bonded compounds, metals and materials for energy applications, with the goal of increasing both the predictive and interpretative power of computer simulations when it comes to understanding the relationships between structure and properties of materials.