In the Materials Informatics Lab, or the MI-Lab, the research revolves around the fusion of data science (AI or machine learning) with materials computations to guide experiments and accelerate design of advanced materials. We primarily utilize first-principles electronic structure methods (DFT), molecular dynamics simulations, and many data-driven techniques, including deep learning, multi-fidelity learning and reinforcement learning. We focus on synthesis of metastable phases, discovery of “green” polymers, and automation of materials laboratories.