معرفی
Jack Jewson is a Senior Lecturer in the Department of Econometrics and Business Statistics at Monash University’s Faculty of Business and Economics, a position he has held since April 2024. He previously conducted postdoctoral research and held a Juan de la Cierva Research Fellowship at Universitat Pompeu Fabra, Barcelona. He is actively accepting PhD students and supervising research in advanced statistical methodologies.
Education:
- PhD in Statistics, University of Warwick (awarded June 2020), in collaboration with the University of Oxford via the Oxford-Warwick Statistics Programme (OxWaSP).
- Integrated Master’s in Mathematics, Operational Research, Statistics, and Economics, University of Warwick (awarded July 2015).
His research focuses on Bayesian inference under model misspecification, particularly in the M-open world, where no true model is assumed to exist. He develops robust computational methods for variable and model selection, and investigates statistical inference under differential privacy constraints. His work integrates loss functions into Bayesian updating and explores graphical and structural modeling applications in economics and biology. These interests are driven by the need for reliable inference in complex, real-world scenarios where models are inherently imperfect.
His recent publications span high-impact journals such as The Annals of Applied Statistics, Biometrics, and Bayesian Analysis, as well as top machine learning venues like NeurIPS. The research demonstrates a strong trend toward robust, privacy-aware Bayesian methods with applications in biostatistics, signal processing, and network modeling. His work bridges theoretical statistics with practical computational solutions for modern data challenges.
Scientific Awards:
- No specific awards or fellowships mentioned in the provided text.
Jack Jewson has not received explicit mention of grants or funding in the text, but his prior Juan de la Cierva Fellowship indicates competitive research support. He is actively mentoring PhD students and expanding his research group at Monash. His work involves collaboration with leading statisticians such as David Rossell, Piotr Zwiernik, Jim Q. Smith, and Chris Holmes. While no formal lab name is provided, his research group focuses on robust Bayesian computation and privacy-preserving inference.
