💡 Research interest

My research focuses on the development and application of statistical methods for complex data, with particular emphasis on robust and permutation-based inference, multiple testing, selective inference, mixed-effects models, and resampling methods. My methodological work is strongly motivated by interdisciplinary questions in social statistics, public health, ageing, welfare, neuroscience, psychology, and environmental health. I focus on statistical tools that provide valid and interpretable inference for complex applied data, including high-dimensional, dependent, heterogeneous, and design-sensitive settings. Recent applications include multimorbidity, health inequalities, occupational risk behaviors, childcare services, multiverse analysis, and environmental determinants of health.

I collaborate with several national and international research groups. I am a member of the Psicostat group at the University of Padova, and the Italian Global Burden of Disease research group (Italian GBD Initiative). I also contribute as a research fellow to the Age-it and Planet4Health projects.

My research activity is complemented by the development of open-source statistical software, including R packages for permutation-based inference, design analysis, Procrustes-based methods, power analysis, and robust inference.

You can download my CV here.