Welcome! We are a multidisciplinary group developing novel computational methods and tools for learning-based decision making and control of complex and unknown dynamical systems that are changing over time. The overarching theme of our work is to harness data collected with available sensors from the system and its environment to enhance the traditional feedback control loop rooted in model-based design with learning enabled components. By doing so, our goal is adapt to changing operating conditions and contexts, and meet control objectives while ensuring safety. Our applications are in biomedical control systems, multi-agent systems, flight control and aerospace control.