Network Science plays a central role in the study of complex systems, offering a range of computational tools and a common language to represent systems as diverse as the World Wide Web, the human brain and social networks. Within this framework, a system is modelled as a set of nodes, representing the individual units of the system, and a set of links, representing the dyadic relationships between these units.

Many networks have been shown to exhibit a complex organization and yet can often be comprehended by simple and universal mechanisms. Our research aims at developing methods and tools in order to extract useful information from network data, at identifying the impact structure on dynamical processes and at enriching the network paradigm, for instance through the study of multiplex, higher-order and temporal networks. 

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