Michele Ceriotti

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michele.ceriotti@epfl.ch +41 21 693 29 39 http://cosmo.epfl.ch/

+41 21 693 29 39
EPFL > VPA-AVP-PGE > AVP-PGE-EDOC > EDMX-ENS

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

+41 21 693 29 39
Office:  MXG 337
EPFL > STI > IMX > COSMO

Web site:  Web site:  https://cosmo.epfl.ch/

EPFL SCITAS-CD
PH A2 364 (Bâtiment PH)
Station 3
1015 Lausanne

+41 21 693 29 39
Office:  PH A2 364
EPFL > VPA-AVP-CP > SCITAS > SCITAS-CD

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Administrative data

Fields of expertise

Atomistic computer simulations, statistical mechanics, machine learning, molecular dynamics, nuclear quantum effects, molecular materials, nucleation. 

Teaching & PhD

Teaching

Materials Science and Engineering

PhD Students

Abbott Joseph William, Bigi Filippo, How Wei Bin, Huguenin-Dumittan Kevin Kazuki, Kellner Matthias Linus, Mazitov Arslan, Nigam Jigyasa, Pozdnyakov Sergey, Rumiantsev Egor, Saade Sandra, Suman Divya,

Past EPFL PhD Students

Anelli Andrea , Baldi Edoardo , Ben Mahmoud Chiheb , Cheng Bingqing , Gasparotto Piero , Giofré Daniele , Goscinski Alexander Jan , Grisafi Andrea , Helfrecht Benjamin Aaron , Imbalzano Giulio , Kapil Venkat , Lopanitsyna Nataliya , Maksimov Dmitrii , Musil Félix Benedito Clément ,

Courses

Introduction to atomic-scale modeling

(Coursebook not yet approved by the section)

Statistical mechanics

(Coursebook not yet approved by the section)

Statistical methods in atomistic computer simulations

The course gives an overview of atomistic simulation methods, combining theoretical lectures and hands-on sessions. It covers the basics (molecular dynamics and monte carlo sampling) and also more advanced topics (accelerated sampling of rare events, and non-linear dimensionality reduction)

Lecture series on scientific machine learning

(Coursebook not yet approved by the section)