Rate My Professor Mark Girolami

Professor Mark Girolami is the Sir Kirby Laing Professor of Civil Engineering in the Department of Engineering at the University of Cambridge, a position to which he was elected in March 2019 following the retirement of Professor Lord Robert Mair. He holds the Royal Academy of Engineering Research Chair in Data Centric Engineering at Cambridge and is a Fellow of Christ’s College, Cambridge. Prior to joining Cambridge, Girolami was Chair of Statistics in the Department of Mathematics at Imperial College London. He serves as Chief Scientist of The Alan Turing Institute since October 2021, having been one of its original founding Executive Directors and subsequently Strategic Programme Director, during which he established and led the Lloyd’s Register Foundation Programme on Data Centric Engineering. Girolami leads the Computational Statistics and Machine Learning Group in the Department of Engineering and acts as Data Lead for the Centre for Smart Infrastructure and Construction. A computational statistician with ten years' experience as a Chartered Engineer within IBM, his research specializations include computational statistics, mathematical statistical methodology, Bayesian statistical methodology, statistical approaches to numerical methods, and applications of probabilistic, stochastic, and statistical modeling in engineering and natural sciences.

Girolami is an elected Fellow of the Royal Academy of Engineering and the Royal Society of Edinburgh. He was an EPSRC Advanced Research Fellow from 2007 to 2012 and an EPSRC Established Career Research Fellow from 2012 to 2018, and he received the Royal Society Wolfson Research Merit Award. In 2023, he was awarded the Guy Medal in Silver by the Royal Statistical Society. He delivered the IMS Medallion Lecture at the Joint Statistical Meeting in 2017, the Bernoulli Society Forum Lecture at the European Meeting of Statisticians in 2017, and the BCS and IET Turing Talk in 2020 across London, Manchester, and Belfast. Girolami served as Editor-in-Chief of Statistics and Computing for a decade and is the founding Editor-in-Chief of the open access journal Data Centric Engineering published by Cambridge University Press. His influential publications include 'Riemann manifold Langevin and Hamiltonian Monte Carlo methods' (2011, Journal of the Royal Statistical Society Series B: Statistical Methodology), 'Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources' (1999, Neural Computation), 'Mercer kernel-based clustering in feature space' (2002, IEEE Transactions on Neural Networks), 'Construction with digital twin information systems' (2020, Data Centric Engineering), and 'Hamiltonian Monte Carlo for hierarchical models' (2015, Current Trends in Bayesian Methodology with Applications).