Welcome to Sam Power who will be joining the Bayes4Health project at Bristol from August 3. Sam arrives having completed a PhD at the University of Cambridge at the Cambridge Centre for Analysis. His research focuses on Monte Carlo methods, numerical analysis, computational statistics and Bayesian modelling, particularly Bayesian nonparametrics. Sam’s recent paper “Accelerated sampling on discrete spaces with non-reversible Markov processes” (arXiv:1912.04681 [1]) provides exciting new practical and theoretical developments on the implementation of continuous-time non-reversible MCMC methods for sampling discrete parameters. These new methods offer improvement over existing state-of-the-art methods on a range of problems from statistics, computational statistics, machine learning and cryptography. Sam is an active twitter user (@sam_power_825) with over 1,800 followers and he regularly posts interesting discussions on statistics and machine learning topics. In Bristol, Sam will work alongside Professor Christophe Andrieu pursuing research in Markov chain Monte Carlo methods, with a focus on the analysis and design of novel sampling methodologies.

[1] Power, S., & Goldman, J. V. (2019). Accelerating Sampling on Discrete Spaces with Non-Reversible Markov Processes In arXiv [stat.CO]. arXiv. https://arxiv.org/abs/1912.04681