Supervisor: Professor Vito Latora
Project description:
Our world today is highly interconnected and dynamical. Social interactions and human mobility affect the way in which ideas, but also transmitted diseases, propagate and can become pandemic. The interconnectedness of financial institutions affects instability and credit crises. Analogously, a single failure can lead to a complete collapse of a power grid through a cascading failure mechanism. We therefore live on this delicate balance in which we would like to have, on the one hand, more social and communication links to better propagate innovation, good social habits and novel technological products but, on the other hand, fewer links to limit the propagation of biological diseases, or to contain cascading failures in critical infrastructures and systemic risk in financial systems.
The purpose of this PhD project is to propose a general framework to analyse and model spreading processes in complex networks. For this we will: 1) distinguish between simple contagion and complex contagion mechanisms, and propose novel models of contagion processes, biological and social epidemics, and cascading failures. We will use complex networks but also higher-order structures, such as simplicial complexes and hypergraphs, to model interactions in groups of size larger than two. 2) find initial seeds and topological patters that favour spreading, but also devise counteracting strategies consisting in minimal changes of the network structure that can contain epidemics or completely inhibit cascading failures. 3) consider practical applications to socio-economic systems and to energy systems. E.g., in power grids, limiting connectivity for the sake of additional security is not always desirable, and highly connected structures (microgrids) are heavily discussed while the overall demand for electric power transmission increases.
The perfect candidate will hold an MSc in applied mathematics, physics or engineering, and will have a good background in network science, and experience with mathematical modelling.
Referances: - Simplicial models of social contagion, Iacopini, Petri, Barrat, Latora, Nature Communications 10, 2485 (2019)- The physics of higher-order interactions in complex systems, Battiston et al., Nat. Phys. 17, 1093 (2021)- Stability of synchronization in simplicial complexes, Gambuzza et al., Nature Communications 12, 1255 (2021)- Inhibiting failure spreading in complex networks, Kaiser, Latora, Witthaut, Nature Communications 12, 3143 (2021)- Dynamically induced cascading failures in power grids, Schafer, Witthaut, Timme, Latora, Nature Communications 9, 1975 (2018)- Multi-layer modelling of adoption dynamics in energy demand management, Iacopini, Schafer, Arcaute, Beck, Latora, Chaos 30, 013153 (2020)- A dynamic approach merging network theory and credit risk to assess systemic risk in financial networks, Petrone, Latora, Scientific Reports 8, 5561 (2018)- Lack of practical identifiability may hamper reliable predictions in epidemic models, Gallo, Frasca, Latora, Russo, Science Advances 8(3):eabg5234 (2022)- On the dual nature of adoption processes in complex networks, Iacopini, V Latora, Front. Phys. 9, 604102 (2021)
Further information:
How to apply
Entry requirements
Fees and funding