Sergio Bacallado

[my two initials]

Statistical Laboratory, D.1.10
Center for the Mathematical Sciences
Wilberforce Rd. Cambridge, CB3 0WB

I am a University Lecturer in the Statistical Laboratory and the Department of Pure Mathematics and Mathematical Statistics at the University of Cambridge. I was previously Stein Fellow in the Department of Statistics at Stanford, where I did my PhD in the School of Medicine.

PhD Studentship Opportunity: Applications are invited for an EPSRC funded industrial CASE PhD Studentship with GlaxoSmithKline starting in the fall of 2017. The aim of the project is to study Bayesian optimisation methods for multi-fidelity stochastic bandits, and apply them to the design of experiments in drug discovery and development. For more details, please see the full advertisement.

Research Interests

I am a statistician specialising in Bayesian methods and Bayesian nonparametrics, in particular. I have a background in Structural Biology, and I have previously worked on applications to molecular dynamics simulations and single-molecule biophysics. More recently, I have developed methods for the analysis of human microbiome studies.

I am 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 I am interested in characterizing the tradeoff between accuracy and computational cost implicit in these algorithmic choices.

I am a member of the Cambridge Strategic Research Initiative in Big Data.