We apply state-of-the-art theoretical methods/models to diverse areas of chemistry, with a focus on materials chemistry. Subfields of interest are nonlinear spectroscopy, catalysis, material interfaces, quantum information science, and electron-spin dynamics. Based on quantum mechanical principles and our electronic structure methods, we are currently developing algorithms for the computation of multi-photon processes in molecules (e.g., interaction with quantum light), the accurate prediction of transition state energy barriers (which has been challenging for standard electronic structure techniques), and the understanding of molecule-surface/nanoparticle interactions (through quantum embedding). Our research strongly overlaps with the fields of quantum science, computation at the nanoscale, machine learning, and statistical mechanics/thermodynamics. Our studies in computational chemistry involve the creative and efficient use of high-performance computing to predict electronic and optical phenomena in single molecules and semiconductors of any dimensionality. We are interested in materials and quantum systems that are relevant to cutting-edge experiments, and in quantum algorithms that could solve challenging problems in chemistry.