Research Interest
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.