Olexandr Isayev

Connecting artificial intelligence (AI) with chemical sciences.


I am an assistant professor at the Department of Chemistry, Carnegie Mellon University. My current research interests focus on solving fundamental chemical problems with machine learning, molecular modeling, and quantum mechanics.

Featured publications:

AFLOW-ML: A RESTful API for machine-learning predictions of materials propertiesComputational Materials Science, 152, 2018, 134-145.
[DOI: 10.1016/j.commatsci.2018.03.075]

Less is more: Sampling chemical space with active learning.
Journal of Chemical Physics 148, 2018, 241733.
[DOI: 10.1063/1.5023802]

 Machine learning for molecular and materials science.
Nature. 2018, 559547–555.
[DOI: 10.1038/s41586-018-0337-2]

ANI-1: an extensible neural network potential with DFT accuracy at force field computational costChem. Sci., 2017, 8, 3192-3203.
[DOI: 10.1039/C6SC05720A]

Deep Reinforcement Learning for De-Novo Drug Design.
Science Advances. 2018. 4 (7), eaap7885.
[DOI: 10.1126/sciadv.aap7885]

Universal fragment descriptors for predicting properties of inorganic crystals. Nature Communications 8, 2017, Article number: 15679.
[DOI: 10.1038/ncomms15679]