About

PhD in explainable AI and uncertainty quantification, applied to healthcare. I lead the data science team at mama health in Berlin, building AI that listens carefully to patients and helps clinicians decide well.

My research sits at the intersection of medical AI, human–AI interaction, and the cognitive science of how people work with intelligent systems — co-authored with the Cabitza lab at the University of Milano–Bicocca on contrasting–evidence explanations, pro–hoc XAI design, and conformal prediction for clinical decision support.

This site is where I think out loud about the parts that don’t fit in a paper: techniques, tools, and notes from the build.

Elsewhere

• github github.com/lorenzofamiglini
• scholar Google Scholar
• linkedin in/lorenzo-famiglini-phd
• x @lorenzofamigli1

Articles here are drafted with AI as a thinking partner and edited by hand. The ideas, framing, and the bits I’m wrong about are mine.