Four Bocconi Projects Funded by the FIS Program
Four researchers from Bocconi University have obtained funding from the Italian Science Fund (FIS) for proposals addressing key issues in theoretical and applied computer science, development economics, and political science. The projects—selected through competitive calls for proposals—will contribute to expanding knowledge in very different areas of research, but all share a focus on complex phenomena and the role of data.
According to Elena Carletti, Dean for Research, “We are delighted that these projects have received support from the Italian Science Fund, as they involve research that addresses complex issues with innovative and rigorous approaches. This is an important recognition of the work and ideas of Bocconi researchers. The funded projects show how scientific curiosity and interdisciplinary openness are central to our approach to research.”
The evolution of gender norms in developing countries
Stefano Fiorin, Department of Economics
The CGNiDC project analyzes how social norms and collective behaviors influence women's economic and political participation. The research combines field experiments, large sample surveys, and administrative data in three very different contexts: Kenya, Indonesia, and Nepal. The topics addressed include the role of working conditions favorable to mothers, the emergence of cultural practices such as the veil in relation to economic opportunities, and the ways in which parties select female political candidates. The goal is to understand which factors favor lasting change in contexts characterized by strong social constraints.
Towards a more unified theory of computational complexity
Adam Polak, Department of Computing Sciences
The BEFINE project addresses some open questions in fine-grained complexity, an area of algorithm theory that studies the speed limits at which known problems can be solved. The project aims to clarify the relationships between three central hypotheses of the discipline, such as 3SUM and APSP, and to introduce new tools for analyzing algorithms 'guided' by predictions provided by machine learning models. This dual theoretical and empirical approach will help define a more solid framework for understanding when algorithmic improvements are realistic and when they encounter structural limits that are difficult to overcome.
How political opinions are formed and what this means for European integration
Guido Tabellini, Department of Economics
The POLEUROPE project studies the formation of political beliefs from different perspectives: the role of social identities, the effects of propaganda, and the communication dynamics of political leaders. Through online experiments, media content analysis, and comparative surveys in European countries, the project aims to understand how citizens' opinions on divisive issues are structured and which narratives influence support for – or resistance to – greater political integration of the European Union. The analysis will also include a comparison of political discourse, school textbooks, and citizens' responses to reconstruct how the interpretative frames of the European project evolve over time.
Understanding gene regulation at single-cell level
Andrea Tangherloni, Department of Computing Sciences
The DECODE project develops a new computational approach to integrate two types of experimental data in order to reconstruct gene regulation networks that are difficult to observe directly. The proposal introduces transformer architectures designed to handle the extremely fragmented and high-dimensional nature of biological data. Applications include the study of the mechanisms that drive T-cell differentiation and the analysis of gene regulation in triple-negative breast cancer, with the ultimate goal of improving tools for interpreting complex cellular processes.
