Updated complete CV

  • Résumé Alex Arenas (2023)

  • Short Vitae

      Doctor of Physical Sciences from the University of Barcelona (1996), he is a Full Professor at the Department of Computer Engineering and Mathematics (DEIM) at the Rovira i Virgili University (URV) since 2010, where he joined in 1995. He is also an External Faculty member at the Complexity Science Hub in Vienna since 2017, and Chief of Complex Systems Science at the Pacific Northwest National Laboratory USA. He has been a visiting researcher at Lawrence Berkeley Laboratory (LBL) and UC Berkeley for 3 years. His scientific career has focused on the study of complex network systems, a multidisciplinary field that he has approached from the perspectives of physics and computation. His curriculum includes numerous publications in the fields of medicine, epidemiology, biology, economics, urban science, technological systems, and social sciences. The result of his research has been the publication of more than 250 articles in international journals, including Nature, The Lancet, Nature Physics, Science Advances, Nature Communications, Physical Review X, and PNAS USA, among others. These articles have received over 37,000 citations according to Google Scholar, with an H-index of 76. He has been the principal investigator in 47 research projects, including two EU FP7 projects and one funded by the James S. McDonnell Foundation. He is an editor of the journal Physical Review E by the American Physical Society, responsible for the Interdisciplinary Physics section, as well as the Oxford Journal of Complex Networks, the MIT Network Neuroscience journal, and the Journal of Computational Social Science. He has served as a reviewer for national (MINECO, ANECA, AGAUR) and international scientific projects (Belgium, France, Switzerland, Argentina, Colombia, USA, UK, Israel), including ERC projects. He has supervised 15 completed doctoral theses and 3 ongoing ones. As scientific recognition, he has been named a Fellow of the American Physical Society (2018):"For foundational research in network science and complex systems — including in community detection, synchronization, and multilayer networks — and his outstanding editorial and mentoring contributions", Fellow of the Network Science Society (2020), recipient of the Mathematics and Society Award from the Ferran Sunyer i Balaguer Foundation (2020), ICREA Academia (2011, 2017, 2023), winner of the "Best Network Communicator" award from Catalunya Ràdio in 2022, the City of Tarragona Scientific Merit Award, and the prestigious Narcís Monturiol Medal in 2022. His performance has been recognized by the Government of Catalonia, which has appointed him as a member of the COVID-19 Advisory Committee in Catalonia and as an advisor for the implementation of the Science Law in Catalonia, as part of the Horitzó group.

    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. 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 epidemiology, 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. In the last years, 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. Also we have a runnig collaboration in the particular field of "personalised medicine", through the analysis of genomic networks, and network medicine.

    Application areas: