Dr Andrea Pizzoferrato

Andrea holds a BSc in Physics and an MSc in Mathematical Physics from "Sapienza" University of Rome, where he conducted research on Equilibrium Statistical Mechanics under the supervision of Prof Francesco Guerra & Prof Adriano Barra. He later earned a PhD in Mathematics from the University of Warwick, focusing on Non-equilibrium Statistical Mechanics and Large Deviation Theory under the guidance of Prof Stefan Grosskinsky & Prof Paul Chleboun.

Andrea’s postdoctoral training began with a joint appointment at the Alan Turing Institute-Imperial College London, where he worked on Predictive Graph Analytics and the Propagation of Information in networks in collaboration with Thomson-Reuters/Refinitiv (now part of the London Stock Exchange Group) advised by Prof Mihai Cucuringu (University of Oxford). He subsequently undertook a second postdoctoral position at the Alan Turing Institute-Queen Mary University of London, where he focused on the simulation of rare-event scenarios in power systems under the supervision of Prof John Moriarty. Andrea’s academic journey continued with his appointment as an Assistant Professor in Mathematics at the University of Bath.

In addition to his research roles, Andrea has been actively engaged in scientific community-building initiatives. He was the main organizer of the "Theory and Methods Challenge Fortnight" scientific retreat on Physics-Informed Machine Learning, held at the Alan Turing Institute (London, UK), as well as a corresponding online workshop (see here for the YouTube playlist). He is also a co-organizer of the "Phi-ML meets Engineering" online seminar series, hosted by the Turing, since its inception.

Andrea’s primary research interests span Statistical Mechanics of Complex Systems (including Neural Networks, Quantitative Sociology, and Blockchain Cybersecurity), Rare Events (with a focus on Large Deviation Theory and Catastrophe Scenario Generation), and Physics-inspired Machine Learning (like Clustering Algorithms).