Filippo Ascolani (PhD candidate in Statistics) and Francesco Gaffi (PhD alumnus and currently postdoctoral fellow at the University of Notre Dame, United States) are among the winners for 2023 of the SBSS Student Paper Award, conferred by the American Statistical Association for innovative contributions in Bayesian statistics. Their work involves statistical models for data featuring a form of dependence known as partial exchangeability, which is appropriate when one wants to aggregate information from different sources or generated under differing experimental conditions. A classic example is the study of patients with a certain disease but treated in different hospitals, who may therefore present some level of heterogeneity.