Dr. Ben Calderhead
Postdoc (with Professor Mark Girolami)
Ben graduated in Mathematics from the University of Glasgow, during which time he also studied Pure Mathematics for one year at the University of Mainz (Germany). He then completed a Masters (by research) in Computational Statistics, before completing a doctorate in Computational Statistics as a Microsoft Research European PhD Scholar, also at the University of Glasgow. Over the last 8 years, Ben has completed a number of business internships including software development at Data Connection (now Metaswitch Networks), business analysis at Procter & Gamble, and financial analysis in M&A at Lazard. He also ran his own computer company and shop for 3 years while at school. He now works as a Research Associate in the Department of Statistical Sciences at University College London.
Ben's work is mainly in the field of computational statistics with applications to systems biology, and his work is largely motivated by real biological problems. In particular he develops Bayesian statistical methodology for tackling the challenging problem of parameter inference and hypothesis testing using a variety of statistical models, including those described by nonlinear differential equations. His current research focuses on developing efficient Markov chain Monte Carlo methods for sampling from high-dimensional and strongly correlated probability densities. Particularly exciting is his recent work developing Riemannian Manifold Langevin and Hamiltonian Monte Carlo methods.