The research focus of the laboratory is to control nonlinear systems using real-time embedded platforms. Our work spans from modeling and system identification of hybrid dynamical systems to control problem formulation, software development, and real-world control implementations. We are particularly interested in deep reinforcement learning and networked control of multi-agent systems. Our current application areas include robotics and autonomous systems. Additionally, we are exploring advanced algorithms for improving the efficiency and robustness of these systems in dynamic and uncertain environments.