Economy and society



The economy and society curriculum concerns data science and artificial intelligence methods applied to the broad area of social sciences as well as the social impact of their applications. The last decades have witnessed the growing accessibility and availability of large and heterogeneous data sources, and an increasing development of computational tools for social data analysis and modelling. The list of topics of potential interest in this curriculum range from the development of statistical models and methods for the analysis of complex data structures to the adaptation and the application of AI to the economic and social science fields. A wide variety of PhD courses focusing on the multi-disciplinary applications and advanced data science and artificial intelligence methodology are offered.

Research Topics

Research topics in this curriculum include the development of novel data integration techniques, statistical learning approaches (Bayesian, semi-parametric and non-parametric), unsupervised learning and clustering, and network analysis algorithms. As far as applications are concerned, we focus on social and economic phenomena, analysis of large scale social surveys, analysis of social networks, detection of fairness and bias in machine learning models.

Expected Outcome

PhD students enrolled in this curriculum will be able to contribute on the development of new data science methods suitable for analyzing social phenomena or they can focus on novel applications of machine learning, artificial intelligence and statistical methods in a variety of social science domains (e.g., economy, sociology, public administration). Graduates in this track will be ready to successfully apply for lead Data Science positions in companies and Public Health agencies, as well as to pursue research careers in both the public and private sectors.

ADSAI people

Curriculum Coordinator: Prof. Domenico De Stefano

Faculty Members

Adjoint Faculty Members