Roger Guimerà Manrique

Roger Guimerà Manrique

Universitat Rovira i Virgili

Experimental Sciences & Mathematics

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).

Research interests

Cells and economies are examples of complex systems. In complex systems, individual components interact with each other 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 analyzing their constituent parts in isolation. 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, using probabilistic approaches taken from statistical physics.
During the last years, Roger's work has turned to exploring the intersection between these probabilistic approaches, Bayesian inference and machine learning. In this area, he has contributed novel methods for interpretable machine learning, and uncovered some fundamental limitations in model-learning.

Selected publications

- Fajardo-Fontiveros O, Reichardt I, De Los Ríos HR, Duch J, Sales-Pardo M & Guimerà R 2023, 'Fundamental limits to learning closed-form mathematical models from data', Nature Communications, 14, 1, 1043.
- Font-Pomarol L, Piga A, Garcia-Teruel RM, Nasarre-Aznar S, Sales-Pardo M & Guimera R 2023, 'Socially disruptive periods and topics from information-theoretical analysis of judicial decisions', Epj Data Science, 12, 2.
- Danús L, Muntaner C, Krauss A,Sales-Pardo M, Guimerà R. 2023, 'Differences in collaboration structures and impact among prominent researchers in Europe and North America', Epj Data Science, 12, 1, 12.
Proceedings of the National Academy of Sciences of the United States of America, 120, 50, e2303887120.

Selected research activities

Active grants:
  • Statistical physics of network inference for interpretable machine learning, MINECO (Spain)
  • Física estadística de selección y validación de modelos para datos complejos, MINECO (Spain)
  • PLoS ONE
Technology transfer agreements:
  • GREENh2PIPES, Enagás (Spain)