ABOUT THE GROUP
We are a computational/theoretical condensed matter physics group in the Department of Physics at Temple University. We use computational and data-driven approaches to understand and design novel quantum phases and functional materials for quantum information science and energy conversion. We use first-principles computations based on density functional theory to understand structure-property correlations and use them to design novel quantum phases in both bulk and two-dimensional materials. Using state-of-the-art AI technologies, we develop machine learning frameworks for solid-state materials and beyond, taking advantage of physical principles such as symmetries and other beyond-atom material information.