Francesco Flora

francesco.flora[at]unina.it

PhD in: MERC
Ciclo: XXXVI

Project title: The Human Exodus: Predicting Human Migration due to Environmental Change

Supervisor(s): prof. Maurizio Porfiri, prof. Manuel Ruiz Marín, prof. Pietro De Lellis

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  • I am currently a Ph.D. student in the Modeling and Engineering Risk and Complexity (MERC) program at the Scuola Superiore Meridionale.
    I graudaded cum laude in Theoretical Physics at the University of Naples Federico II, discussing a thesis on the role of chromatin 3D architecture inside eukaryotic cells and the effects of Structural Variants on its correct folding.

    This project has its foundations in the urgent problem of understanding why, how and when people decide to migrate.

    Human migration is a complex and very important problem in social science: many drivers seem to contribute to people’s decision to move away from their home. For this reason, it is very difficult to develop a predictive model complete and mathematically solid, yet simple enough, to serve as a practical tool to international institutions.

    At the present time, there are some important model that made significant steps in trying to predict human mobility, yet they are not complete enough in considering the main drivers of this complex process. In particular, environmental change is now one of the major causes associated to human mobility but, because the interdependencies between environmental conditions and human mobility  are not well understood, a complete theory of environmental human migrations (EHM) accounting for different drivers  is still missing.

    In this project, using tools from complex networks, dynamical systems, spacial analysis, risk management and data analysis, we will try to bridge the gap between environmental models and human migrations models, building a mathematically principled framework able to predict human migrations considering all the main factors that enter into the decision process, and which can be used as standard tool by international institutions to predict future scenarios and evaluate and mitigate the risk associated to them.