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Alexander Shapeev
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Research
Machine-Learning Interatomic Potentials
Machine Learning for Computational Materials Discovery
First-principles calculations of alloy phase diagrams using Machine Learning
Prediction of chemical reaction rates using Machine Learning
Modelling cathodes using Machine Learning
Machine Learning for Elastic Strain Engineering
Atomistic-to-Continuum Coupling
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2020
2019
2018
News (15)
21/05/2020
Our paper is in the top-cited list of Journal of Chemical Physics
16/04/2020
Patent is published
05/02/2020
RFBF grant: Machine learning the thermodynamics of complex materials with ab initio accuracy
14/12/2019
Our paper is on the cover of Journal of Chemical Physics issue
02/10/2019
Konstantin Gubaev defense
24/06/2019
MSc student defenses
15/06/2019
Our paper is among top 20 most read articles in SIAM MMS
06/06/2019
AMLIPMD workshop
26/05/2019
Media on our artificial intelligence algorithm accelerating quantum calculations
01/05/2019
Our paper is among the most cited papers in Computational Materials Science
20/03/2019
Neural network strains to confer novel properties on materials
09/10/2018
RFBR grant
28/09/2018
Discovering new alloys 1000 times faster
25/05/2018
New superconducting allotropy of boron
04/04/2018
RScF grant