Prof. Alex Arenas (Barcelona, 1969) PhD in Physics. He is full professor at Dept. Computer Science and Mathematics (DEIM), Universitat Rovira i Virgili (URV). In 2000 and 2008, he was visiting professor at the Lawrence Berkeley Lab. (LBL). He is editor in charge of Interdisciplinary Physics in APS Physical Review E. He got the J. McDonnell Foundation award for the study of complex systems in 2011. He was also recognized as ICREA Academia-Institució Catalana de Recerca i Estudis Avançats, in 2011 and 2017. He serve as Editor in J. of Complex Networks, J. of Computational Social Science and in Network Neuroscience. He is external faculty of the Complexity Hub Science in Vienna from 2017. In 2019, he was elected as Fellow of the American Physical Society. In 2020, he has was elected Fellow of the Network Science Society. During the COVID-19 pandemic he has been providing scientific advice to the Gobierno de España, and the Generalitat de Catalunya.
Research interests
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. The applicability of the understanding of basic phenomena underlying these systems have direct applications in epidemiology, neuroscience, social sciences, systems biology and computer science. Specifically, I am particularly interested on the study of dynamic transitions in complex systems, and in developing algorithms and/or tools to analyze the collective behavior of different dynamical models on networks. Lately, our activity has focused on the spatio-temporal evolution of epidemics in networked systems, with special emphasys on COVID-19, consolidating a line of research in computational epidemiology. In this endevour we have bridged theory with real application.
Keywords
Epidemic spreading, mathematical modelling, complex networks, multiplex networks, modular structure, synchronization, game theory