Olexandr Isayev

Olexandr Isayev is the Carl and Amy Jones Professor in Interdisciplinary Science in the Department of Chemistry at Carnegie Mellon University. His research focuses on Machine Learning and Computational methods. Isayev's work bridges theoretical chemistry, pharmaceutical sciences, and computer science, utilizing molecular simulations and artificial intelligence to address complex chemistry problems. His lab develops machine learning potentials that approximate quantum mechanical calculations and generative AI methods for inverse design problems. He is affiliated with several programs, including the CMU-Pitt Computational Biology Ph.D. Program and the Scott Institute for Energy Innovation. Isayev's research has contributed to the development of accurate and efficient models for molecular simulations and drug design.

Olexandr Isayev is a Carl and Amy Jones Professor of Chemistry at Carnegie Mellon University, specializing in computational chemistry, AI for science, drug discovery, and materials informatics. His research focuses on developing machine learning models to predict molecular and materials properties with high accuracy, enabling advancements in drug design and materials science. He has pioneered deep learning approaches for molecular simulations, such as the ANI neural network potential, which achieves density functional theory accuracy at force field computational costs. His work emphasizes the integration of AI with quantum mechanics and the application of active learning to explore chemical space efficiently.