Oscar´s research interests lie at the intersection of nonlinear control theory and its engineering applications. A central theme of his work is the design of observers for nonlinear systems, with particular emphasis on homogeneity-based and sliding mode approaches, including bi-homogeneous observers for mechanical systems of varying degrees of freedom. He has made contributions to output feedback control of nonlinear systems. His work further extends to fault detection, notably the development of adaptive observer-based methods for inter-turn short-circuit fault detection in permanent magnet synchronous motors (PMSMs). He has also explored distributed optimization and network control, through finite-time convergent primal-dual gradient dynamics based on the multivariable super-twisting algorithm. Currently, his research focuses on distributed observer design for state estimation and monitoring of multi-energy systems, as well as optimal control and energy management of integrated multi-energy systems.