Our group works at the intersection of condensed matter physics, computational materials science, and artificial intelligence, developing multiscale theories and data-driven methods for complex quantum materials. We combine first-principles calculations, effective models, many-body numerical simulations, and machine learning to explore high-temperature superconductivity, strongly correlated electron systems, low-dimensional magnetism, multiferroicity, and magnetoelectric coupling. Our goal is to identify new mechanisms, predict novel properties, and discover new materials across vast materials spaces.
We welcome students and collaborators with backgrounds in physics, materials science, computing, mathematics, or artificial intelligence to help build an open, interdisciplinary, and forward-looking research platform for intelligent quantum materials.