{"id":313,"date":"2023-12-04T18:07:11","date_gmt":"2023-12-04T17:07:11","guid":{"rendered":"https:\/\/datascience.unifi.it\/eccellenzadisia\/?page_id=313"},"modified":"2026-02-18T14:30:10","modified_gmt":"2026-02-18T13:30:10","slug":"about","status":"publish","type":"page","link":"https:\/\/datascience.unifi.it\/eccellenzadisia\/about\/","title":{"rendered":"About"},"content":{"rendered":"
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The research objectives focus on developing statistical methods for complex data and causal inference that can be used as decision-support tools in specific domains; these tools should be interpretable, guarantee excellent predictive capabilities, and quantify uncertainty. These methods will provide comprehensive support for scientific knowledge and discovery in the Department’s domains of interest, such as demography, social sciences, economic phenomena, medicine, and epidemiology.<\/p>\n\n\n\n

The main training objective concerns the strengthening of highly qualified educational programs and the training of excellent researchers. ReDS pursues the objectives of knowledge transfer to actively contribute to the innovation and technological development processes of the economic and social context of which the Department is part. To this end, ReDS also promotes professional training by promoting and stimulating interactions between DiSIA researchers and all those interested in project topics belonging to the academic and non-academic world.<\/p>\n\n\n\n

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Scientific objectives<\/h2>\n\n\n
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Causal Analysis in Data Science<\/h3>\n\n\n\n

The first scientific objective of the project concerns the design and analysis of experimental and observational studies for causal analysis in light of the new challenges in data science and artificial intelligence. To answer questions of a causal nature, the ideal tool is represented by randomized experiments which cannot always be conducted: in the current era of Data Science, observational studies, including studies characterized by high-dimensional data and complex structures, represent a precious source for causal analysis, but they also pose new challenges and difficulties.<\/p>\n\n\n\n

ReDS will allow us to achieve the following scientific objectives:<\/strong><\/p>\n\n\n\n