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.
Delft University of Technology
Faculty of Technology, Policy and Management
Building 31
Jaffalaan 5
2628 BX Delft
The Netherlands
This project has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under the
Marie Skłodowska-Curie grant agreement number 955708.