I am an Associate Professor in 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.

Sergio Bacallado

sb2116 at cam.ac.uk

Statistical Laboratory
Department of Pure Mathematics and
Mathematical Statistics
University of Cambridge
Centre for Mathematical Sciences D1.10


I am a statistician specialising in Bayesian nonparametrics and algorithms for Bayesian inference. I am broadly interested in applications of Statistics and Machine Learning in structural biology, chemoinformatics, human microbiome studies, and the design of clinical trials. I have developed methods for the estimation of reversible time-series, with applications in the analysis of molecular dynamics simulations. I have also worked on Bayesian nonparametric models for compositional data in microbiome studies. More recently, I have been interested in applications of deep learning and language models in drug discovery, and in the study of remote homology of protein sequences.

I am a member of the Cambridge Centre for AI in Medicine and the Cantab Capital Institute for the Mathematics of Information.




I have lectured the following courses at Cambridge. Course materials can be found on Moodle.

  • Part IB Statistics
  • Part II Statistical Modelling
  • Part III Bayesian Modelling and Computation
  • Part III Modern Statistical Methods
Plain Academic