Complexity and Networks

The last decade has witnessed a paradigm shift in the social and natural sciences, fuelled by unprecedented amounts of data collected by various sensors and electronic devices. This shift has led to the gradual disappearance of the boundaries between scientific disciplines - e.g. computer science, statistical physics, applied mathematics, social sciences - and to the emergence of universal tools and theories that allow addressing the complexity around us.

Large-scale data tend to have a relational netare, and their complexity often lies in the web of connection between their elements. Our research group studies the organisation and dynamics of such complex networks. Based on empirical observations in social and brain networks, our research aims at developing computational tools to uncover and visualize information in networked systems, as well as a theoretical framework for dynamical processes on dynamical networks. Applications include: cascades of information in online media, fMRI brain networks, large-scale social networks, human mobility.

Cool stuff

We gave a tutorial about Network Analysis in the Age of Large Network Dataset Collections at CIKM 2017.

The book Diffusion on temporal networks (World Scientific) is out!

Participating at ECCS, have a look at the program of our satellite Coarse-graining of Complex Systems.

Diffusion on temporal networks: How does temporality affect diffusion on networks? Implications for community detection and model reduction.

OpenStreetCab: Should you take a Yellow Cab or Uber?

L'Arbre de Diane Editions: Maison d'Edition sur les interactions entre sciences et littérature.