
Encourages students to think outside the box.
Inspires students to love learning.
Makes learning interactive and engaging.
Always supportive and understanding.
Jack Jewson serves as Senior Lecturer in the Department of Econometrics and Business Statistics within Monash Business School at Monash University, having joined in April 2024. Previously, he held a Juan de la Cierva Research Fellowship from March 2022 to February 2024 at Universitat Pompeu Fabra (UPF) in Barcelona, following a two-and-a-half-year postdoctoral research assistantship there from September 2019 to March 2022, collaborating with Dr. David Rossell and Dr. Piotr Zwiernik at the Barcelona School of Economics. Jewson obtained his PhD titled "Bayesian Inference in the M-open world" from the University of Warwick through the Oxford-Warwick Statistics Programme (OxWaSP), supervised by Prof. Jim Q. Smith at Warwick and Prof. Chris Holmes at Oxford; he submitted in September 2019 and was awarded the degree in June 2020. Earlier, he completed an Integrated Master's degree in Mathematics, Operational Research, Statistics, and Economics at the University of Warwick in July 2015.
His research specializes in Bayesian methods for high-dimensional inference problems where full Bayesian analysis is infeasible, emphasizing approximations at modeling or computational levels. Key areas include robust inference under model misspecification in the M-open framework, loss functions and divergences for Bayesian belief updating and decision-making, variable and model selection, graphical and structural modeling, and differentially private statistical inference. Applications span economics and biology. Prominent publications are: "On the stability of general Bayesian inference" with J.Q. Smith and C. Holmes (Bayesian Analysis, 2024); "Graphical model inference with external network data" with L. Li et al. (Biometrics, 2024); "Bayesian sparse vector autoregressive switching models with application to human gesture phase segmentation" with B. Hadj-Amar and M. Vannucci (Annals of Applied Statistics, 2024); "Differentially private statistical inference through β-divergence one posterior sampling" with S. Ghalebikesabi and C. Holmes (NeurIPS, 2023); "Bayesian approximations to hidden semi-markov models for telemetric monitoring of physical activity" with B. Hadj-Amar and M. Fiecas (Bayesian Analysis, 2023); and "General Bayesian loss function selection and the use of improper models" with D. Rossell (Journal of the Royal Statistical Society Series B, 2022). Jewson was awarded the Juan de la Cierva Research Fellowship. He currently accepts PhD supervision in robust Bayesian inference, computational Bayesian selection methods, and privacy-constrained inference.