I am Staff Research Scientist in Machine Learning at DeepMind.

I received a Diploma di Laurea in Mathematics from University of Bologna and a PhD in Machine Learning from École Polytechnique Fédérale de Lausanne (IDIAP Research Institute). I worked in several Machine Learning and Statistics research groups: the Empirical Inference Department at the Max-Planck Institute for Intelligent Systems (Prof. Dr. Bernhard Schölkopf), the Machine Intelligence and Perception Group at Microsoft Research Cambridge (Prof. Christopher Bishop) and the Statistical Laboratory, University of Cambridge (Prof. Philip Dawid).

My research interests are based around Bayesian & causal reasoning, graphical models, variational inference, time-series models, deep learning, and ML fairness and bias.


  • Temporal degeneracy in recommender systems -- a theoretical analysis. Accepted to the ACM Conference on AI, Ethics, and Society, 2019.
  • Path-specific counterfactual fairness. Accepted to AAAI-2019.
  • Comparing interpretable inference models for videos of physical motion, AABI 2018.
  • Safe Machine Learning: Specification, Robustness, and Assurance, ICLR Workshop, 2019.