Stefano Cortinovis

I am a PhD student in the Department of Statistics at the University of Oxford, supervised by François Caron and Mark van der Wilk. My research sits at the intersection of statistics and machine learning, with a focus on uncertainty quantification and Bayesian inference.

A recurring theme in my work is Bayes-assisted methodology: incorporating prior information into frequentist procedures to improve their efficiency while maintaining their guarantees. In this context, I have been working on e-values and prediction-powered inference, developing methods that provide reliable uncertainty statements while leveraging modern ML models in sequential workflows. Looking ahead, I am excited to explore conformal prediction and generative modelling from similar perspectives.

Beyond research, I enjoy taking an active role in the communities I am part of. I serve as student representative for the StatML CDT, and I help organise the Oxford Young Statisticians Seminar and the E-values Reading Group at Oxford Statistics.

Before coming to Oxford, I studied at Bocconi University in Milan, where I completed a BSc in Economics and Computer Science and an MSc in Data Science under the supervision of Igor Prünster. Outside of work, I like running in pretty places and reading random Wikipedia entries.

If you’d like to chat, feel free to reach out via email or LinkedIn!