Michele Ceriotti

Michele Ceriotti

École Polytechnique Fédérale de Lausanne

H-index: 65

Europe-Switzerland

About Michele Ceriotti

Michele Ceriotti, With an exceptional h-index of 65 and a recent h-index of 55 (since 2020), a distinguished researcher at École Polytechnique Fédérale de Lausanne, specializes in the field of Atomic-scale modeling, Machine learning, Materials science, Statistical mechanics, Physical chemistry.

His recent articles reflect a diverse array of research interests and contributions to the field:

Smooth, exact rotational symmetrization for deep learning on point clouds

Mechanism of charge transport in lithium thiophosphate

A prediction rigidity formalism for low-cost uncertainties in trained neural networks

Thermal transport of LiPS solid electrolytes with ab initio accuracy

Completeness of atomic structure representations

Accelerated chemical science with AI

Electronic Excited States from Physically Constrained Machine Learning

Uncertainty quantification by direct propagation of shallow ensembles

Michele Ceriotti Information

University

Position

Associate Professor at Institute of Materials

Citations(all)

15189

Citations(since 2020)

11930

Cited By

7469

hIndex(all)

65

hIndex(since 2020)

55

i10Index(all)

151

i10Index(since 2020)

140

Email

University Profile Page

École Polytechnique Fédérale de Lausanne

Google Scholar

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Michele Ceriotti Skills & Research Interests

Atomic-scale modeling

Machine learning

Materials science

Statistical mechanics

Physical chemistry

Top articles of Michele Ceriotti

Title

Journal

Author(s)

Publication Date

Smooth, exact rotational symmetrization for deep learning on point clouds

Advances in Neural Information Processing Systems

Sergey Pozdnyakov

Michele Ceriotti

2024/2/13

Mechanism of charge transport in lithium thiophosphate

Chemistry of Materials

Lorenzo Gigli

Davide Tisi

Federico Grasselli

Michele Ceriotti

2024/2/5

A prediction rigidity formalism for low-cost uncertainties in trained neural networks

arXiv preprint arXiv:2403.02251

Filippo Bigi

Sanggyu Chong

Michele Ceriotti

Federico Grasselli

2024/3/4

Thermal transport of LiPS solid electrolytes with ab initio accuracy

arXiv preprint arXiv:2401.12936

Davide Tisi

Federico Grasselli

Lorenzo Gigli

Michele Ceriotti

2024/1/23

Completeness of atomic structure representations

APL Machine Learning

Jigyasa Nigam

Sergey N Pozdnyakov

Kevin K Huguenin-Dumittan

Michele Ceriotti

2024/3/1

Accelerated chemical science with AI

Seoin Back

Alán Aspuru-Guzik

Michele Ceriotti

Ganna Gryn'ova

Bartosz Grzybowski

...

2024

Electronic Excited States from Physically Constrained Machine Learning

ACS Central Science

Edoardo Cignoni

Divya Suman

Jigyasa Nigam

Lorenzo Cupellini

Benedetta Mennucci

...

2024/2/29

Uncertainty quantification by direct propagation of shallow ensembles

arXiv preprint arXiv:2402.16621

Matthias Kellner

Michele Ceriotti

2024/2/26

Robustness of local predictions in atomistic machine learning models

Journal of Chemical Theory and Computation

Sanggyu Chong

Federico Grasselli

Chiheb Ben Mahmoud

Joe D Morrow

Volker L Deringer

...

2023/11/10

Wigner kernels: body-ordered equivariant machine learning without a basis

arXiv preprint arXiv:2303.04124

Filippo Bigi

Sergey N Pozdnyakov

Michele Ceriotti

2023/3/7

Physics-inspired equivariant descriptors of nonbonded interactions

The Journal of Physical Chemistry Letters

Kevin K Huguenin-Dumittan

Philip Loche

Ni Haoran

Michele Ceriotti

2023/10/20

2021 JCP Emerging Investigator Special Collection

The Journal of Chemical Physics

Michele Ceriotti

Lasse Jensen

David E Manolopoulos

Todd Martinez

David R Reichman

...

2023/2/14

Modeling the ferroelectric phase transition in barium titanate with DFT accuracy and converged sampling

arXiv preprint arXiv:2310.12579

Lorenzo Gigli

Alexander Goscinski

Michele Ceriotti

Gareth A Tribello

2023/10/19

scikit-matter: A suite of generalisable machine learning methods born out of chemistry and materials science

Open Research Europe

Alexander Goscinski

Victor Paul Principe

Guillaume Fraux

Sergei Kliavinek

Benjamin Aaron Helfrecht

...

2023

Surface segregation in high-entropy alloys from alchemical machine learning

Journal of Physics: Materials

Arslan Mazitov

Maximilian A Springer

Nataliya Lopanitsyna

Guillaume Fraux

Sandip De

...

2023/10/11

A data-driven interpretation of the stability of organic molecular crystals

Chemical Science

Rose K Cersonsky

Maria Pakhnova

Edgar A Engel

Michele Ceriotti

2023

Fast evaluation of spherical harmonics with sphericart

The Journal of Chemical Physics

Filippo Bigi

Guillaume Fraux

Nicholas J Browning

Michele Ceriotti

2023/9

Natural aging and vacancy trapping in Al-6xxx

Journal of Materials Research

Abhinav CP Jain

M Ceriotti

WA Curtin

2023/12/21

Modeling high-entropy transition metal alloys with alchemical compression

Physical Review Materials

Nataliya Lopanitsyna

Guillaume Fraux

Maximilian A Springer

Sandip De

Michele Ceriotti

2023/4/26

A machine learning model of chemical shifts for chemically and structurally diverse molecular solids

The Journal of Physical Chemistry C

Manuel Cordova

Edgar A Engel

Artur Stefaniuk

Federico Paruzzo

Albert Hofstetter

...

2022/9/23

See List of Professors in Michele Ceriotti University(École Polytechnique Fédérale de Lausanne)

Co-Authors

H-index: 75
David Manolopoulos

David Manolopoulos

University of Oxford

H-index: 73
Gabor Csanyi

Gabor Csanyi

University of Cambridge

H-index: 60
Jörg Behler

Jörg Behler

Georg-August-Universität Göttingen

H-index: 55
Marco Bernasconi

Marco Bernasconi

Università degli Studi di Milano-Bicocca

H-index: 47
Giovanni Bussi

Giovanni Bussi

Scuola Internazionale Superiore di Studi Avanzati

H-index: 38
Thomas Markland

Thomas Markland

Stanford University

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