Combines machine learning and first-principles simulation to predict properties, design magnetic and quantum materials, and model charge and spin transport. Develops exchange–correlation and kinetic-energy functionals, high-throughput screening, and data-centric imaging to accelerate discovery across materials and physical chemistry.