Projects per year
Personal profile
Research summary
Carlotta Montorsi joined LISER on September, 15th 2020 as a PhD Candidate for the Living Conditions Department. She will work within the DTU DRIVEN multi-disciplinary framework working on the "Predicting well-being in old age" project supervised by Alessio Fusco, Philippe Van Kerm and Stéphane Bordas. The project aims at idenfying predictors of well-being in old age across European Countries by means of machine learning algorithm. Carlotta is also enrolled at Insubria University (Varese, Italy) where she undertakes the Phd Doctoral Program in Methods and Models for Economic decision.
Carlotta undertook a Master degree in Economics and Social Sciences at Bocconi University, Milan (Italy). She subsequently worked as research fellow at Insubria University, Varese (Italy), where she investigated well-being determinants in Italy at provincial and national level, as well as micro-simulation models applied to Italy.
Carlotta is an Italian citizen and speaks Italian, English and Spanish.
Education/Academic qualification
Economics and business, Master, Bayesian multilevel models for energy demand and supply assessment in rural Nepal municipalities, Bocconi University
Award Date: 26 Oct 2019
Network
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Projects
- 1 Active
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DRIVEN: Data-driven computational modelling and applications
FUSCO, A., Beex, L., Billieux, J., Bordas, S., D'Ambrosio, C., Del Sol, A., Francis, O., Hale, J., Pang, J., Peters, B., Sauter, T., Skupin, A., Theobald, M., Tkatchenko, A., Van Dam, T., Viti, F., Vögele, C., Zilian, A. & MONTORSI, C.
Luxembourg Institute of Socio-Economic Research (LISER), Fonds National de la Recherche-FNR
1/09/18 → 31/08/25
Project: Research
Research output
- 1 Article
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La resilienza del sistema italiano di protezione sociale all'inizio della crisi COVID-19: evidenze territoriali
Translated title of the contribution :The resilience of the Italian social protection system at the beginning of COVID-19 outbreak: territorial evidence Research output: Contribution to journal › Article › peer-review