Research in computational electrochemistry — bridging first-principles simulations, statistical thermodynamics, and machine learning to understand catalytic surfaces.
Machine-learning molecular dynamics applied to energy materials and structural ceramics — connecting atomistic simulations to electrochemical and mechanical observables.
Peer-reviewed articles in computational electrochemistry, machine learning potentials, and surface science. h-index 7 · 1089 citations.
Biography, curriculum vitae, and contact information.