Dr. Medford is interested in leveraging materials informatics, statistics, and machine learning to maximize the practical impact of fundamental atomic-scale simulations in the field of surface science and catalysis. His research areas include heterogeneous catalysis, oxide surface chemistry, density functional theory, kinetic models, uncertainty quantification, and Bayesian optimization and inference.
Professor Medford’s teaching interests involve kinetics, thermodynamics, numerical methods, and data analytics.
PhD, Stanford University, 2015
BS, textile engineering, N.C. State University, 2009
Y Kim, H Locht, AJ Medford, CW Jones, Boron-tuned tetrahedral Co (II) sites in zeolite beta enhance propane dehydrogenation, Applied Catalysis B: Environment and Energy, 126077, 2025
AJ Medford, TN Whittaker, B Kreitz, DW Flaherty, JR Kitchin, Prospects for Using Artificial Intelligence to Understand Intrinsic Kinetics of Heterogeneous Catalytic Reactions, arXiv preprint arXiv:2510.18911, 2025
S Bhowmik, AJ Medford, P Suryanarayana, A Sharma, JE Pask, Ab initio study of strain-driven vacancy clustering in aluminum, Physical Review B 112 (17), 174105, 2025
K Sakai, I Furikado, AJ Medford, Rational design of selective catalysts for ethylene hydroformylation via microkinetic modeling and universal neural network potentials (vol. 450, 116253, 2025), JOURNAL OF CATALYSIS 452, 2025
S Bhowmik, AJ Medford, P Suryanarayana, Real-space Hubbard-corrected density functional theory, The Journal of Chemical Physics 163 (23), 2025