Shedrack Akpe is a computational catalysis researcher working at the interface of density functional theory and machine learning. His previous work focused on heterogeneous catalyst design, kinetic modeling, and mechanistic studies of hydrogenation, dehydrogenation, and hydrodeoxygenation for biomass-to-fuel and other sustainable chemical processes. He is now building foundation models for transition-metal catalysis, using string representations of metal complexes and transformer models to learn how catalytic cycles behave under different conditions.