Welcome to the online home of the Control and Optimization for Renewables and Energy Efficiency (CORE) Lab! We are a research lab that specializes in the application of advanced optimization and control algorithms to emerging problems in renewable energy and energy efficiency. Our control “toolbox” focuses especially on hierarchical control, model predictive control, economic optimal iterative learning control, and the application of machine learning tools to real-time optimal control, though we have proficiency in a variety of advanced control techniques and always seek to bring the appropriate technique to the table when addressing a new application. Presently, our lab is focused on applying control and optimization tools to airborne (tethered) wind energy systems, tethered marine hydrokinetic energy systems, and energy-efficient connected and autonomous vehicles. Thus, we are revolutionizing energy harvesting and efficiency in the air, on the ground, and underwater!