We are interested in studying the hybrid materials by a combination of computational strategies and first-principles approaches, including density functional theory (DFT), time-dependent DFT, nonadiabatic molecular dynamics, and many-body perturbation theory. We focus on the structural, electronic, and photophysical properties of advanced material systems (e.g., inorganic semiconductors, topological insulators, TMDs, and inorganic/hybrid perovskites) with different dimensionality and functions. We are also interested in machine learning (ML) for the discovery of new materials for light-emitting, photovoltaic, and spintronic applications.