Welcome message
Welcome to my webpage, where you can explore two of my greatest passions: teaching and research. Engaging in these activities brings me immense satisfaction. On this page, you'll find information about both endeavors. Beyond academia, I also have fun doing many other activities, including traveling, watching movies, indulging in good food, reading, and getting lost in big cities. Two favorites of mine are Madrid (my hometown) and Lisbon (my second hometown), both perpetually worth a visit.
Short Bio
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I received the degree in Telecommunications Eng. and the doctorate degree (together equivalent to the B.Sc., M.Sc., and Ph.D. degrees in Electrical Eng.) with highest honors from the Carlos III University of Madrid, Madrid, Spain, in 2002 and 2007 respectively. Two years of my Ph.D. program were carried out at the University of Minnesota, USA. In 2007, I became a faculty of the Department of Signal Theory and Communications, King Juan Carlos University, Madrid, Spain, where I currently develop my research and teaching activities as a Professor. From 2007 to 2015 I visited (under different roles) the Department of Electrical Eng. at the University of Minnesota, USA. In 2015, 2016 and 2017 I was a Visiting Scholar at the Department of Electrical and Systems Eng. at the University of Pennsylvania, USA. |
Teaching
Teaching, to me, is one of the most rewarding tasks humanity can undertake. Teaching engineering, in particular, brings even greater pleasure. Engineering involves employing intuition, mathematics, and science to solve non-trivial problems. It's about leveraging technology to enhance the society we inhabit and, at times, shaping the future that lies ahead.
Research
At the core of my research lies the application of (stochastic) signal processing, machine learning, and non-linear optimization (especially duality theory and dynamic programming). I apply these concepts to the domains of intelligent networks, artificial intelligence, and network science. Presently, I am increasingly intrigued by understanding the relationship between data science and graph theory. The development of signal processing and machine learning algorithms tailored to graphs and networks holds significant promise for the burgeoning fields of intelligent and dynamic networks, social networks, and big data.
