Bayesian Analysis and Modelling Workshop 2026

Description

Hosted by Monash Business School, Department of Econometrics and Business Statistics in partnership with Melbourne Business School, The University of Melbourne this annual workshop, presented by both international and local Bayesian experts, is open to anyone interested in Bayesian statistics and econometrics.

Research presentations encompass development of state-of-the-art Bayesian techniques, as well as applications of Bayesian analysis of contemporary issues. The workshop will be preceded by a masterclass on contemporary topics.

PhD Poster Submission

Our workshop will include the annual PhD Poster Prize. A judging panel of senior researchers will evaluate submitted posters, and the winner will be announced at the workshop’s conclusion.

We invite you to submit your poster abstract by clicking on the link below.

Submit your poster here

Event Registration

Please click here to register to attend the event, registratons close 30 October 2026.

Register here

Key Dates

Keynote Speaker

Associate Professor David Nott, National University of Singapore 

A/Prof Nott is an internationally recognised leader in Bayesian statistics and computational methodology. His research expertise includes variational inference in high-dimensional models, model misspecification and robust Bayesian inference, and development of state-of-the-art modular inference methods for handling complex models. He has an extensive publication record in top-tier journals including the Journal of the American Statistical Association, Biometrika, and the Journal of Econometrics and Bayesian Analysis. His work has had substantial impact across statistics, econometrics, and machine learning, and he is widely regarded as a leading contributor to modern Bayesian computation.

Speakers

Dr Linda S Tan, National University Singapore  

A/Prof Tan is an Assistant Professor in the NUS Department of Statistics and Applied Probability. Her research focuses on advances in Bayesian inference, with particular focus on variational approximation of hierarchical and mixed models using stochastic optimisation. Asst/Prof Tan is an influential mid-career researcher whose contributions are shaping how Bayesian methods scale to modern data settings. She has published in top-field journals such as the Journal of Royal Statistical Society, the Journal of Computational and Graphical Statistics and Bayesian Analysis. Her publications are well-regarded within the field, especially among those working on computational Bayesian methods.

Dr Gregor Zens, Research Scholar, International Institute for Applied Systems Analysis (Austria)  

Dr Zens’ research expertise centres on Bayesian econometrics and computational statistics applied to social and economic problems. His work focuses on developing scalable Bayesian methods — such as variational inference, model averaging, and advanced MCMC techniques — for high-dimensional and structured data, with applications in areas like human migration, demography, and global development. His publication record in leading journals, such as the Journal of the American Statistical Association, Bayesian Analysis, and the Journal of Royal Statistical Society, and ongoing work on scalable Bayesian inference and latent variable models, position him as an emerging researcher at the intersection of Bayesian methodology and applied social science.

Workshop Speakers

• Prof Rodney Strachan, University of Queensland
• Prof Dino Sejdinovic, Adelaide University
• Prof Minh Ngoc Tran, University of Sydney
• A/Prof Clara Grazian, University of Sydney
• Dr Matias Quiroz, University of Technology Sydney
• Dr David Gunawan, University of Wollongong
• Dr Leah South, Queensland University of Technology
• Dr Takuo Matsubara, University of Sydney