Roger Guimerà (Barcelona, 1976) graduated in Physics at Universitat de Barcelona in 1998, and obtained a PhD in Chemical Engineering from Universitat Rovira i Virgili in 2003. He then moved to Northwestern University where he worked as a postdoctoral fellow and, later, as a Fulbright Scholar. In 2008 he became a Research Assistant Professor at Northwestern's Department of Chemical and Biological Engineering, before accepting his current position at ICREA in 2010. He has been awarded the Premi Nacional de Recerca al Talent Jove (2010), the Erdös-Rényi Prize in Network Science (2012), and the Young Scientist Award for Socio- and Econophysics (2014).
Cells, ecosystems and economies are examples of complex systems. In complex systems, individual components interact with each other, usually in nonlinear ways, giving rise to complex networks of interactions that are neither totally regular nor totally random. Partly because of the interactions themselves and partly because of the interaction’s topology, complex systems cannot be properly understood by just analyzing their constituent parts. This feature of complex systems poses important challenges from both a fundamental perspective and an engineering perspective. Roger’s research is devoted to the study of complex systems and, particularly, of the structure of complex networks and the interplay between network structure and dynamics. During his career, he has: (i) made methodological contributions to the study of complex networks, and (ii) used complex network analysis to gain understanding on a number of systems.
– Tarres-Deulofeu M, Godoy-Lorite A, Guimera R & Sales-Pardo M 2019, ‘Tensorial and bipartite block models for link prediction in layered networks and temporal networks’, Physical Review E, 99, 3, 032307.
– Menden MP et al. 2019, ‘Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen‘, Nat. Comm. 10, 2674
– Senan O, Aguilar-Mogas A, Navarro M, Capellades J, Noon L, Burks D, Yanes O, Guimera R, Sales-Pardo M 2019, ‘CliqueMS: a computational tool for annotating in-source metabolite ions from LC-MS untargeted metabolomics data based on a coelution similarity network‘, Bioinformatics, 35, 20, 4089 – 4097
– Godoy-Lorite A Guimerà R & Sales-Pardo M 2019, ‘Network-Based Models for Social Recommender Systems‘. In: Moscato P, de Vries N (eds) Business and Consumer Analytics: New Ideas. Springer, Cham
Selected research activities
– “Mecánica Estadística para el Modelado y la Predicción del Comportamiento Humano”, (MINECO), 1 Jan 2017 – 30 Jun 2020
Invited talks at international conferences:
– 10th International Conference on Complex Networks, COMPLENET’19, Tarragona, Catalonia
– Workshop on Higher-order Interaction Networks, Oxford, UK
– Critical and Collective Effects in Graphs and Networks 2019, Les Houches, France
– PLoS ONE