corso di dottorato "Analysis of Complex Networks: Structure and Dynamics"




February 20-22, 2013, Politecnico di Milano

Scientific course organized by

DEIB - Politecnico di Milano


SICC - Italian Society for Chaos and Complexity

A network is a set of agents pairwise connected by links. Despite the

simplicity of this definition, the theoretical properties of networks

are extremely rich and diversified. Most notably, networks turn out to

be extremely flexible in modeling a wide variety of phenomena

characterized by a large number of interconnected elementary units:

social networks, the Internet and the WWW, sensor networks, ecological

communities, biochemical systems, energy transportation networks,

economic and financial networks, are just but a few examples.

The course is part of the teaching activities organized by the PhD

Program in Information Technology at Politecnico di Milano, yet it is

not only addressed to PhD students, but to all researchers working in

any areas of science and engineering and interested in the theory and

applications of complex networks. The aim is to illustrate the

fundamental theoretical notions as well as a number of applications in

specific fields. The basic definitions, a few useful indicators, and the

most important network models are first introduced ("structure"). Then,

dynamical systems interacting through the network will be considered, to

illustrate how phenomena such as epidemic/information diffusion or

large-scale consensus and synchronization can be dealt with ("dynamics").


Renato Casagrandi, Politecnico di Milano

Fabio Dercole, Politecnico di Milano

Fabrizio De Vico Fallani, CNRS UMR-7225, CRICM - Hôpital de La

Pitié-Salpêtrière, Paris

Mario Di Bernardo, University of Naples "Federico II"

Giorgio Fagiolo, Sant'Anna School of Advanced Studies, Pisa

Carlo Piccardi, Politecnico di Milano

Sergio Rinaldi, Politecnico di Milano

Alessandro Rizzo, Politecnico di Bari

Roberto Tempo, CNR-IEIIT, Politecnico di Torino


- Networks and their topology. Distance, diameter, clustering

coefficient, degree distribution, measures of centrality. Network

models: random, small-world, scale-free. Community analysis

- The PageRank computation in Google, randomized algorithms, web

aggregation and consensus of multi-agent systems

- The international-trade network: empirical evidence and modeling

- Networks in the brain

- Contact processes on networks: dynamics of epidemic diseases

- Networks of dynamical systems and collective behaviors

- Emergence of spatial patterns and Turing instability

- Master-slave synchronization

- Master Stability Function approach

- Connection Graph Stability method

- Topological indicators of synchronization propensity

- Evolution of biological networks toward synchrony and chaos

- Adaptation and evolution for synchronization and control of complex


- Consensus-based distributed estimation in sensor networks