Our research focuses on the development of numerical optimization algorithms, control theory, and machine learning methods for decision-making problems (e.g., control, operation, planning, and design) in energy systems (e.g., energy storage/conversion systems, power grids, natural gas networks, and district heating/cooling systems). Our goal is to create scalable computational frameworks that will help decarbonize our energy infrastructure.