New Technologies and Developments in Unmanned Systems

Engineering from UPM, and Fluid Mechanics from the von Karman Institute for Fluid Dynamics. In 2013 she completed her Ph.D. in Aerospace Engineering at UPM. Her research focuses on computational fluid dynamics and the development of novel tools for data analysis enabling the detection of spatio-temporal patterns. Recently, she has developed reduced-order models taking advantage of the insights provided by data analysis tools. In addition, she has contributed to the fields of flow control, global stability analysis, analysis of flow structures in complex flows (transitional and turbulent) using data-driven methods, and prediction of temporal patterns using machine learning and soft computing methods. She has published more than 80 scientific contributions (articles, proceedings, and book chapters), written two books, and supervised 15 undergraduate/master and two Ph.D. students. She is the primary investigator (PI) of the (Spanish) National Project NEMDAEA and PI of the MSCI Doctoral Network European projects MODELAIR (PI-Coordinator) and ENCODING (PI-UPM). These three projects aim to develop new machine learning tools and models to reduce environmental pollution by improving aircraft efficiency, reducing air pollution in cities, and improving the efficiency in turbulent combustion, respectively. 



Xin Chen, Ph.D., is currently an Assistant Professor at the Telecommunications Engineering School of Universidad Rey Juan Carlos. Prior to that, she was a visiting investigator at the Massachusetts Institute of Techology and a visiting professor and the "Juan de la Cierva Formacíon" postdoctoral researcher at the Universidad Carlos III de Madrid. Dr. Chen received a Bachelor's degree in Electrical Engineering and Automation from Shanghai University in 2007 with the Outstanding Graduate Award, a Master's degree in Aerospace Engineering from Università di Pisa and Universidad Politécnica de Madrid in 2009 with a full scholarship from the Europe