ESR11 – Data-driven support to understanding of complex dynamical physical phenomena, such as epidemics

ESR11: Data-driven support to understanding of complex dynamical physical phenomena, such as epidemics

Recruiting beneficiary: University of Torino, Italy 

 

Internal supervisors: Prof. Maria Luisa Sapino, Prof. Matteo Sereno

 

Brief project description: In this project, the ESR will: (i) develop a learning framework to assist decision makers, suitable for the complicated dynamics of the systems interconnected under epidemic scenarios and the highly heterogeneous systems, varying in spatial and temporal scales data; (ii) improve and refine the above framework, to take into account the peculiarities of complex natural and human-based systems, such sparse and noisy observations; (iii) develop efficient sampling algorithms that, with limited available simulation budget (and therefore inherently sparse model results), allow to capture the main characteristics of the dynamically evolving system of interest.