Bio
Luke is a PhD student in the Department of Statistical Science at University College London working with Dr Samuel Livingstone and Prof. Gianluca Baio. His research focuses on Bayesian computation for survival models, with applications in Health Technology Assessment.
He holds a Bachelor’s degree in Mathematics and Statistics from the University of Warwick and a Master’s degree in Statistics from University College London, where for his dissertation project he developed Bayesian models to help improve exercise rehabilitation sessions for mechanically ventilated ICU patients. During his PhD studies he has completed an internship working in health economic modelling at Parexel and has previously worked at a medical research charity.
Research interests
Luke’s research focuses on the development of novel Markov Chain Monte Carlo methods based on continuous-time Piecewise Deterministic Markov Processes (PDMPs), and the application of these new methods to advanced Bayesian survival models. Recently PDMP methods have been developed to efficiently sample from the transdimensional posteriors in Bayesian variable selection problems. Luke’s work has focused on extending these approaches to develop PDMP-based versions of split-merge, birth-death reversible jump MCMC schemes, and applying these methods to polyhazard models, a flexible class of survival model.
Luke is interested in increasing the applicability of PDMP samplers to more complex problems, particularly in the context of transdimensional sampling problems, and extending polyhazard models to incorporate a wider range of features observed in survival analysis.