Cancer evolution

I am an assistant professor at the University of British Colubmia in the Departments of Computer Science and Pathology and a scientist in the Department of Molecular Oncology at the British Columbia Cancer Agency.


My research is primarily focused on the development and application of statistical and machine learning methods for analysing cancer omics data. The methods I develop leverage probabilistic graphical models and non-parametric Bayesian methods to extract biologically interpretable quantities from complex datasets. I am also interested in developing computationally efficient inference algorithms to fit these models. I am particularly interested in variational and sequential Monte Carlo methods. These two themes support the ultimate goal of my research which is to understand evolutionary cancer biology.

Selected papers


  • PyClone - Software for inferring clonal population structure from bulk genomics sequencing.

  • SCG - Software for inferring clonal population structure from noisy single cell sequencing.

  • PGSM - Implementation of the efficient particle Gibbs split merge algorithm for inference in Dirichlet process mixture models.