Expertise
Computational chemistry, Machine Learning, Nonequilibrium Assembly, Biomimetic Active Matter; Computational Nanoscience
Education
- Doctor of Philosophy (Ph.D.), Molecular Physics and Chemistry, University of Paris-Saclay
Biosketch
Jerome Delhommelle, Ph.D., completed his undergraduate studies at the Ecole Normale Supérieure of Paris-Saclay (France) and earned a Ph.D. in Molecular Physics and Chemistry from the University of Paris-Saclay. He is the recipient of a National Science Foundation (NSF) CAREER Award from the Division of Materials Research and an Outstanding Young Faculty Award from the Division of Computers in Chemistry of the American Chemical Society.
His research group is currently supported by the NSF (Division of Chemistry), the Department of Energy (Materials Sciences and Engineering Division) and the American Chemical Society (ACS). He also received the Departmental Teaching Excellence Award for developing AI and machine learning courses within the chemistry curriculum. Delhommelle co-authored the introductory textbook "A Mole of Chemistry" (CRC Press) and a graduate textbook, "Molecular Networking: Statistical Mechanics in the Age of AI and Machine Learning" (CRC Press).
He recently served as chair of the Topical Group on Data Science (GDS) of the American Physical Society and as North American editor of "Molecular Simulation." In this capacity, and in collaboration with Martin Karplus, Ph.D., 2013 Nobel Laureate in chemistry, he developed a series of special issues on “Free Energy Simulations.” He is the co-author of more than 120 peer-reviewed publications, and his work has appeared on the covers of prestigious journals, including the "Journal of the American Chemical Society" and "Physical Review Letters."