Complex Networks

Due to the rapid evolution of the World Wide Web and the increase of information technology infrastructures the study of complex network structures became an emerging interdisciplinary research area. Also, collective behavior research has been largely driven by the availability of increasingly large amounts of data.

The challenge of understand the collective behavior of systems summed with their inherent complexity are factors that explain the increasing interest in enhancing complex network tools which enables us to capture structural features of the networks in a systematic manner. The data representation in complex networks permits to unify the structural complexity and vertex and connection diversities, but the study of dynamics in complex networks continues to emerge regarding:

to understand how large ensembles of dynamical systems interacting through a complex topology can behave collectively,
to develop dynamical models of how the collectives behave and
to analyze the structure of networks at multiple scales.

This working group is particularly interested in articulating the study of complex networks with machine learning, decision theory, social and communication systems and coupled biological and chemical systems.