Captions are available for this talk. You can remove these by pressing CC on the video toolbar.
Bayesian statistics is now an established tool of trade for an applied statistician or data scientist. However, there are many open challenges in Bayesian modelling and analysis, which are often inspired by challenging real-world problems. In this presentation, Kerrie Mengersen discussed a suite of environmental and biological problems that have required us to build better Bayesian tools to address increasingly sophisticated insights. The applied challenges range from the Antarctic to the Amazon, and from water to wellness. The tools include spatio-temporal models, nonparametrics, latent variable constructs and Bayesian network analyses. The work is based on research with a range of collaborators who will be acknowledged in the presentation.
Kerrie Mengersen is a Distinguished Professor in Statistics at the Queensland University of Technology in Brisbane, Australia. She is the Deputy Director of the Australian Research Council Centre of Excellence in Mathematical Frontiers and the Director of the QUT Centre for Data Science. Kerrie is also an elected Fellow of the Australian Academy of Science and the Australian Academy of Social Sciences, and a member of the Statistical Society of Australia and the IMS, ASA, RSS, ISBA and ISI. Her research interests are in mathematical statistics and its application to substantive challenges in health, environment and industry, with particular focus on Bayesian methods.
Follow the Centre for Statistics on Twitter