Dr Ben Calderhead
Ben Calderhead, a pivotal part of the Cervest team since 2017, is one of the world’s foremost experts in Bayesian uncertainty quantification and computational statistics. Focused on developing state-of-the-art, computationally efficient statistical methods, he is passionate about using machine learning to tackle complex real-world prediction problems.
A leader in this field for more than a decade, Ben is an assistant professor and lecturer at Imperial College London, teaching statistical modelling and machine learning, and supervising PhD research on Monte Carlo methodology, probabilistic numerics and Bayesian volatility modelling in financial markets. Prior to this he was a visiting researcher at both Harvard and MIT (in 2013 and 2014), and a Research Fellow at UCL. He has given invited talks at leading research institutes around the world, including at Stanford, Harvard, Oxford, Cambridge, and the Alan Turing Institute in London.
With more than 1500 citations to his name in world-leading academic journals and conferences, including Proceedings of the National Academy of Sciences, NIPS, Bayesian Analysis, Biophysical Journal and Journal of the Royal Statistical Society, Ben is extensively published on topics including Markov chain Monte Carlo methodology, single ion channel modelling, and statistical inference using differential equations.
Ben holds a PhD and MSc in Computational Statistics, funded by a Microsoft Research scholarship, and an MSci in Mathematics from the University of Glasgow (2002-2010).