I hold a Degree in Informatics Engineering (Grado en Ingenieria Informatica) by the School of Informatics (FIB) of the Universitat Politecnica de Catalunya (UPC). My PhD Thesis "Evolution and Dynamics in Information Networks" was advised by Prof. Ricard Sole within the Doctorate Program of the Physics Department at the UPC. After a post-doctoral stay in Toulouse (France), I am now Visiting Assistant Professor at the Department of Experimental and Health Sciences (UPF) and member of Institute of Evolutionary Biology (UPF-CSIC). I have active research collaborations with members of the Universite Paul Sabatier (Prof. Guy Theraulaz, Research Center on Animal Cognition), Georgia Tech (Prof. Joshua Weitz, School of Biology), Universitat Politecnica de Valencia (Prof. Santiago F. Elena, Evolutionary Systems Virology Group), UPF (Prof. Jordi Mestres) and the Santa Fe Institute (Prof. Cris Moore).
As the leader of this line of research in the Complex Systems Lab, my goal is to understand the origins of innovation in technological systems, with an emphasis in information networks. Software is the invisible, and yet the most important, technology for our society and we need quantitative, testable theories of software evolution and development. In this context, we have pioneered the study of software systems modeled as complex networks. We think there are important biological lessons to be learned from the study of software systems.
Technological evolution is a crucial component of culture and allows us expanding our capacities beyond any other species ever did and we have a quite good record of it. However, we are still far from having a quantitative theory of technological change, particularly when comparing with evolutionary theory since Darwin. Are there selection forces similar to those present in nature? Is history as relevant in understanding technological evolution? To what extent is innovation the result of tinkering and recombination? My current project (Spanish National Grant FIS2013-44674-P) is a recent example of this type of research.
My research concerns the evolution of natural and artificial networks. How optimality principles, tinkering and constraints shape network organization? For example, we have proposed that network modularity and motif abundances can be obtained "for free" when networks evolve with common rules of duplication and rewiring. We are exploring the role played by spatial embedding in distributed growth and dynamical processes on top of networks. As the byproduct of our research we are going to publish a book on complex networks together with our Netlab software.
Artificial life addresses the main goal of biology, i.e., understanding life, by developing artificial systems that exhibit life-like properties. For example, can we develop artificial systems that exhibit creativity and innovation? In this context, we are embracing these questions by the exploration of standard systems like Avida and developing our own physically-based artificial life systems (Chimera).