Complessità nei sistemi sociali

I am teaching this course at University of Torino. Here you can find the links to the notes and other useful material for the course.

Course notes

• Lesson 1: Temporal graphs
• Lesson 2: Epidemics on networks
• Lesson 3: Cavity method
• Lesson 4: Graph Fourier transform
• Lesson 5: Community detection
• Lesson 6: Node2Vec

Master thesis proposals

Here are some projects that can be explored under my supervision as master thesis. If you are interested in collaborating, drop me an email.

Appropriate contact matrix representations for epidemic modeling

^{Accurate mathematical modeling is a crucial step for better understanding epidemic propagation and to design efficient non-pharmaceutical prevention strategies. Infectious diseased are propagated though a network of contacts that is, however, very hard to estimate. Moreover, even if it was available, it would typically not be possible to share it for privacy concerns. In this project we investigate how to design appropriate contact matrices that can be shared complying with high privacy preserving standards but that, in the meantime, provide a faithful description of the epidemic dynamics.}

Embedding traffic networks

^{The system of roads serving a city can naturally be represented as a network. In this project, we investigate how the road network properties impact the traffic flow over it. We leverage on network embedding techniques to understand similarities and dissimilarities between different cities and to propose impactful policies for the city design to decrease the C02 emission.}

Temporal graph analysis

^{Most systems that can be modeled as graphs have a temporal component and are well modeled by temporal graphs, rather than by static ones. In this project we devise and adopt powerful techniques to analyze temporal graphs and thus the related systems they represent.}