Data-Driven Materials Informatics

Statistical Methods and Mathematical Analysis

Description

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Materials informatics is an emerging field defined by the use of simulation tools combined with methods from data sciences and machine learning to better understand materials properties and design innovative materials. The models which are considered cover an extremely wide range, from Schrödinger’s equation, which describes matter at the (sub)atomistic scale, to the equations of continuum mechanics. Mathematical sciences play a key role in materials informatics, both to construct the databases used to train machine learning algorithms (since these databases are made of reference simulation results), and to harness them in order to extract the most relevant information. The aim of this program is bring together a diverse scientific audience, both between scientific fields (physical sciences, materials sciences, biophysics, etc) and within mathematics (mathematical modeling, numerical analysis, statistics and data analysis, etc), to make progress on key questions of materials informatics.

Organizers

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C D
Claudia Draxl Humboldt-Universität zu Berlin
R K
Risi Kondor The University of Chicago
M M
Marina Meila University of Washington
D P
Danny Perez Los Alamos National Laboratory
G S
Gabriel Stoltz Ecole des Ponts and Inria
F W
Francois Willaime French Alternative Energies and Atomic Energy Commission (CEA)

Program Workshops

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