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Mike's research and teaching activities are in a number of areas of Bayesian statistics involving methodology development and applications of complex stochastic modelling in higher-dimensional problems. Core areas of modelling research relate to theory and methods of multivariate analysis, latent structure, high-dimensional inference and computation, stochastic computational methods, time series modelling, among others.
Inter-disciplinary application areas have included research in signal processing, finance, climatology and neurosciences, among others. Recent and current collaborative projects focus heavily in biomedical research using genome technologies, including pathway studies in cancer and the use of genomic data in clinical studies.
The links at the left lead to information on research - including collaborative inter-disciplinary projects - papers, teaching, study and employment opportunities, as well as friends and intellectual family.
Bayesian dynamic modelling
as author at International Society for Bayesian Analysis (ISBA) Lectures on Bayesian Foundations, Kyoto 2012,
together with: Michael I. Jordan (introducer),