My research is focused on developing algorithms using learning-based control strategies to design safe and robust autonomous systems that interact with the physical world. Machine learning models deployed in practice need stability, performance, robustness, and safety guarantees. Thus, to accurately identify dynamical systems, these properties are formulated as constraints using theoretical foundations of nonlinear control, including Lyapunov-based methods, control barrier functions, and optimization-based control.