We apply state-of-the-art artificial intelligence and machine learning techniques, including deep learning and reinforcement learning, to solve challenging and impactful computational problems in complex cyber-physical systems, such as transportation and power systems, focusing on sequential decision-making under uncertainty and combinatorial optimization.