M. Ángeles Serrano
ICREA Research Professor@UB
The essence of complexity is summarized by the old aphorism coined out more than two thousand years ago: «The whole is more than the sum of its parts» (Lao Tse, Tao Te Ching, VI BC; Aristotle, Metaphysics, IV BC). Complex systems consist of a large number of components interacting in such a way that the group as a whole may produce nonlinear unexpected responses, often exhibiting phase transitions, cascades, crises, catastrophes, and other critical and extreme events. These emergent behaviors come along with other amazing features, like self-organization into hierarchical or multiscale structures, self-similarity, self-regulation, memory, or the ability to adapt and to learn.
Networks are graph representations of real-world complex systems. We are using networks to unravel the basic principles underlying the structure, function, and evolution of complex systems, and to model and predict them.