We aim to drive breakthroughs in energy-efficient technologies and quantum materials discovery through advanced chemical theory. We work at the intersection of theoretical chemistry, machine learning (ML), and materials science. Our research focuses on developing advanced theoretical chemistry frameworks and chemistry-informed ML methods to address challenges in (a) the electrification of the chemical industry and catalysis, and (b) the design and understanding of quantum materials and quantum information science. We develop new theories for predicting how geometry shapes material properties and create chemistry-informed ML approaches to uncover the mechanisms of electrochemical processes and quantum information storage. Group members will gain expertise in chemical theory development, computational chemistry and materials science methods (such as DFT and molecular dynamics), and state-of-the-art AI/ML algorithms.