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, the Machine Intelligence and Perception Group at Microsoft Research Cambridge, and the Statistical Laboratory, University of Cambridge.

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

NEWS:

  • Path-specific counterfactual fairness, AAAI-2019.
  • Comparing interpretable inference models for videos of physical motion, AABI 2018.
  • Safe Machine Learning: Specification, Robustness, and Assurance, ICLR Workshop, 2019.