Prof. Alex Arenas (Barcelona, 1969) got his PhD in Physics in 1996. In 1995, he got a tenure position at Dept. Computer Science and Mathematics (DEIM) at Universitat Rovira i Virgili, and in 1997 he became associate professor at the same department. In 2000, he was visiting scholar at the Lawrence Berkeley Lab. (LBL) in the Applied Mathematics group of Prof. Alexandre Chorin (University of California, Berkeley). After this visit, he started a collaboration with Berkeley, and in 2007 he became visiting researcher of LBL. Arenas has written more than 160 interdisciplinary publications in major peer reviewed including Nature, Nature Physics, PNAS, Physics Reports and Physical Review Letters, which have received more than 9000 citations. He is one of the few Europeans serving as Associate Editors of the most important publication in physics worldwide, the American Physical Society journal, Physical Review. He is in charge of the Complex Networks and Interdisciplinary Physics section of Physical Review E. He got the James Mc Donnell Foundation award for the study of complex systems in 2011. He was also recognized as ICREA Academia-Institució Catalana de Recerca i Estudis Avançats, a catalan award that promotes the most recognized scientists from Catalonia. He serve as Editor in Journal of Complex Networks, and in Network Neuroscience. He was elected for the Steering Committee of the Complex Systems Society in 2012. He is the leader of the research group ALEPHSYS.
My research interests are currently focused on the physics of networked multilevel complex systems. The comprehension of the interplay between the structure of the connectivity and the functionality of networked system is a major challenge for the physics of this era. Concepts that applied to the nowadays classical network theory, must be revisited in the framework of multilevel coupling scenarios, in what is being known as the physics of multilayer networks. The applicability of the understanding of the basic phenomena underlying these systems have direct applications in neuroscience, social sciences, systems biology and computer science. Specifically, I am particularly interested on the study of dynamic transitions in complex networks from a functional multilayer approach. It includes two complementary parts, building a complex networked framework for the analysis of activity signals and proposing physical models to validate the framework. I aim at creating a comprehensive mathematical formalism for constructing a functional time-varying multilayer network (whose layers are functional networks) from activity (eventually time-series) observations. Specific models, algorithms and/or tools will be developed to analyze the collective behavior of different models. Other fundamental aspect to develop concerns the acquisition and processing of data for the study of real systems. This it is an important issue given the strong interdisciplinary component that it implies, nowadays, to study complex networks trying to operate to the maximum of our experience in this field and trying to obtain the maximum possible scientific impact of our results.