Dr Sergio Bacallado is a lecturer in the Statistical Laboratory and the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. Sergio was previously Stein Fellow in the Department of Statistics at Stanford, where he did his PhD in the School of Medicine.

Sergio is a statistician specialising in Bayesian methods and Bayesian nonparametrics, in particular. He has a background in Structural Biology, and has previously worked on applications to molecular dynamics simulations and single-molecule biophysics. More recently, Sergio has developed methods for the analysis of human microbiome studies. He is also interested in the problem of scaling Bayesian computations to modern applications in biology and more broadly. These problems increasingly require algorithms for approximate inference, such as variational Bayesian methods and approximate Bayesian computation, and he is interested in characterising the trade-off between accuracy and computational cost implicit in these algorithmic choices.