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Contact details +64 (06) 356 9099 ext. 84642
I am Professor of Statistics and Chair of the Statistics and Bioinformatics Group in the Institute of Fundamental Sciences.
If you are looking for advice on which statistics paper(s) to take, then feel free to contact me. If you are considering doing Honours or a PhD in Statistics and think that you might like to be supervised by me, then read about my research below.
About My Research
I have a variety of research interests. These include:
I have long been interested in kernel smoothing problems, and in particular spatially adaptive methods for multivariate data. My current work in this area includes kernel estimation of relative risk functions in geographical epidemiology, with former PhD students Sarojinie Fernando and Tilman Davies (the latter now a lecturer at the University of Otago). Recently I have been working in collaboration with Berwin Turlach on weighted density esimation and kernel deconvolution problems. I have also become interested in constrained spline smoothing, again working in conjunction with Berwin, and also with PhD student Khair bin Jones.
Biostatistics and Applied Statistics
I have a keen interest in the development and application of statistical methods in medicine, particularly epidemiology and opthalmology. I am currently working with PhD student Brigid Betz-Stablein and Professor Bill Morgan (Lions Eye Institute, Western Australia) on some challenging statistical modelling problems for ophthalmic data collected from glaucoma patients. I am also a Principal Investigator in Massey's Infectious Disease Research Centre (IDReC), where my work includes modelling patterns of foot and mouth disease in Vietnam with epidemiologist A/Prof Mark Stevenson and PhD student Kate Richards, and estimation of spatial risk (as discussed under Smoothing Methods above).
Through my interests in smoothing, networks, and geographical epidemiology, I have an evolving interest in spatial statistics. Much of Tilman Davies' later work was in this area.
Statistical Modelling and Inference in Transportation Science
Transportation science generates a huge range of fasinating problems. I'm currently focused on the development of new tools for inference in network based models, based on a unified statistical linear inverse framework (tying in with my work on deconvolution smoothing problems, which share the same kind of structure at an abstract level) and modelling and inference for day-to-day dynamic traffic networks (with Professors David Watling, Giulio Cantarella, Hong Lo and Mike Smith, and my former PhD student Katharina Parry, now a lecturer at AUT). From 2009-2011 this research was supported by a New Zealand Royal Society Marsden Fund grant.
In addition to these medical areas, I have a general interest in the application of statistical methods. Indeed, one of the great things about working in statistics is that I've had the opportunity to look at a diverse range of intriguing problems from a wide variety of areas, from archaeology, to finance, to zoology.
Design – for Commerce, Community and Culture, Health and Well-being
Field of research codes
Applied Statistics (010401): Biostatistics (010402):
Civil Engineering (090500): Engineering (090000):
Mathematical Sciences (010000):
Medical And Health Sciences (110000): Public Health and Health Services (111700):
Statistical Theory (010405): Statistics (010400): Stochastic Analysis and Modelling (010406):
Transport Engineering (090507)
Project Title: Modelling, inference and prediction for dynamic traffic networks
Date Range: 2015 - 2019
Funding Body: Royal Society of New Zealand
Project Title: New Tools for Statistical Inference for Network-based Transportation Models
Date Range: 2009 - 2012
Funding Body: Marsden Fund - Full
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Last updated on Friday 23 June 2017