Rate My Professor Brenda Vo

Vo's expertise encompasses theoretical and applied Bayesian statistics, particularly in health and cell biology applications. Her research interests include agent-based models, Approximate Bayesian Computation, multivariate statistical methods, mathematical biology, and health statistics. Ongoing projects feature statistical inferential techniques for agent-based models of Chlamydia infection in guinea pigs, simulations of general practitioner distribution in New South Wales, modeling Q fever notifications linked to livestock movement and factors affecting immunisation rates, and evaluation of the Living Well Multicultural Lifestyle Modification Program. She teaches probability and stochastic modelling, statistical inference, statistical methods in health, and statistical learning, and co-supervises three PhD students on Bayesian methods for ion-selective electrode sensors, ecology and management of vegetable weeds in Australia, and outmigration with agrarian transitions in Myanmar. Key publications comprise 'Quantifying uncertainty in parameter estimates for stochastic models of collective cell spreading using approximate Bayesian computation' (Mathematical Biosciences, 2015), 'Melanoma cell colony expansion parameters revealed by approximate Bayesian computation' (PLoS Computational Biology, 2015), and 'Bayesian parametric bootstrap for models with intractable likelihoods' (Bayesian Analysis, 2018). Vo belongs to the International Society for Bayesian Analysis, Statistical Society of Australia, Q Fever Research Consortium, and NSW Health Technology Assessment Working Party.