Monday, 18 May, morning (9.30-12.30)
Introduction to complex networks (Piccardi): What is a (complex) network. Types of networks and their representation. Quantifying network properties: Distance, diameter, clustering coefficient, degree distribution, centrality. Network models: random (Erdos-Rényi), scale-free (Barabási-Albert), small-world (Watts-Strogatz).
Monday, 18 May, afternoon (14.30-17.30)
Temporal networks (Holme): Types and representations of temporal networks. Spreading processes. Data sets and algorithms. Randomization techniques. Measures of temporal network structure. Open problems and future challenges.
Tuesday, 19 May, morning (9.30-12.30)
Community detection in networks (Fortunato): Introduction. Basic notions of communities and partitions. Modularity optimization, limits. Local approaches. Testing methods. Consensus clustering. Testing the zero-postulate: annotated versus real clusters.
Tuesday, 19 May, afternoon (14.30-17.30)
Multilayer networks (Kivelä): Introduction and background. Conceptual and mathematical framework. Classifying multilayer networks. Data and tools. Models, methods, diagnostics, and dynamics.
Wednesday, 20 May, morning (9.30-12.30) and afternoon (14.30-17.30)
Complex financial networks (Battiston): The lectures cover the main theoretical notions to understand network models of financial contagion. Some time is also devoted to practical exercises with provided software-tools (Gephi and Matlab) introducing the students to the analysis of empirical financial networks and to simple stress-tests on real financial networks.
Thursday, 21 May, morning (9.30-12.30) and afternoon (14.30-17.30)
Contagion dynamics: epidemics on networks (Colizza, Moreno): Infectious diseases modeling: background and principles. Homogeneous mixing. Contact networks. Advanced modeling topics. Applications to real epidemics.
Friday, 22 May