My research is in the field of trustworthy AI and aims at the development and analysis of AI systems that are robust, reliable and appropriable. In particular, my research can be situated at the intersection of uncertainty management, machine learning and human-AI interaction, and regards both the theoretical and foundational aspects of the discipline, as well as applications in high-risk sectors (primarily, healthcare). I'm primarily interested in (and authored publications related to): Learning under uncertainty; Cautious inference and uncertainty quantification; Uncertainty modeling; Imprecise probabilities; Learning theory; Conformal prediction; Fair, Accountable and Transparent ML; Applications of ML and uncertainty modeling in medical decision-making; Human-AI interaction and user-centered AI.