He leads a cross-functional team of engineers and scientists in the development of Amazon SageMaker, a world-class managed platform enabling data scientists and developers to easily build, train, and deploy machine learning models at scale.
Valerio holds a PhD in Machine Learning from the Oxford-Warwick Statistics Programme (OxWaSP), where he was part of the Oxford Statistical Machine Learning group (OxCSML). During his PhD he interned at Amazon, Berlin, and at DeepMind, London, working in the Science team on deep learning for protein folding prediction.
Valerio's expertise is in the areas of machine learning, statistics, deep learning and AI systems. He is interested in developing algorithms and services for large-scale machine learning and Bayesian models for data-driven decision making, with the goal of democratizing artificial intelligence. He has applied his work to automatic ML, computer vision, natural language processing, meta-learning, and fairness, authoring 25+ peer-reviewed papers in top-tier journals, conferences and workshops.