Ryan graduated from the University of Leeds in 2018 with an MMath Mathematics degree, where he took a particular interest in statistical theory and methodology. He commenced his doctoral studies at the Institute in September 2018, under the supervision of Murray Pollock, Gareth Roberts and Petros Dellaportas. His areas of interest include computational statistics, Monte Carlo methods and Bayesian theory.
Ryan’s current research focuses on Monte Carlo Fusion, which aims to tackle the problem of unifying distributed analyses and inferences from multiple sources on shared parameters, into a single coherent inference. This problem may arise in several settings such as expert elicitation, multi-view learning and differential privacy. A prominent example of this challenge appears in the context of ‘big data’, where for computational feasibility, typical MCMC cannot be conducted on a single machine. Ryan is particularly interested in working in a big data setting to construct efficient parallelised schemes to scale up common Monte Carlo algorithms.
Achievements and awards
Ryan was awarded the Royal Statistical Society Prize in 2018 for his performance in his MMath Mathematics degree at the University of Leeds.