|Position:||Senior Lecturer in Statistics|
|Address:||Dept. of Mathematical Sciences,
University of Durham,
Durham DH1 3LE,
|Phone:||(0191 or +44 191) 3343076|
|FAX:||(0191 or +44 191) 334 3051|
Since November 2004, I have been providing statistical advice to the European Food Safety Authority's Panel on "Plant Health, Plant Protection Products and Their Residues". This is fundamentally an inter-disciplinary activity and much of the interest lies in finding pragmatic solutions to difficult problems. I have worked on two scientific opinions on: (i) variability factors for use in assessment of risk to human beings from pesticide residues in fruit; and (ii) uncertainty factors for inter-species variability in sensitivity to pesticides in relation to risk assessment for new compounds. This work has involved collaboration with the members of the EFSA panel, in particular Andy Hart who leads the Risk Analysis group at CSL (the UK's Central Science Laboratory which is part of the UK Government Department for Environment, Food and Rural Affairs).
Funded by the UK Engineering and Physical Sciences Research Council from 2001-04 was research into adsorption of pollutants on contaminated land. The goal of the project was to understand what attributes of pollutant and soil drive variability in adsorption so that these attributes can be incorporated into models used for risk assessment in relation to contaminated sites. More details can be found from the project description page.
Until 2001, my main area of research was methodology for modelling, calibration and forecasting for complex systems which have simulators which are used to understand their behaviour. Examples of such systems are oil reservoirs, gas and oil pipelines and areas of land contaminated by pollutants. What these and many other systems have in common is that the best way to understand the future behaviour of the system is to use a simulator, a computer implementation of a mathematical model for the system. The problem is that as part of the construction of a simulator, values have to provided for a great many quantities which describe physical, chemical, geological and other aspects of the system, quantities about which there is often a great deal of uncertainty. There is usually some data related to these quantities; for example one might have laboratory measurements of aspects of soil samples or the results of seismic or other sub-surface imaging. There may also be relevant expert opinion. Finally there will often be some historical data on the behaviour of the system which may be used to help calibrate the simulator by comparing it to the results of simulator runs for the historical period. For more detail, see the web page for our research group which has worked since 1993 on Bayesian methods for large physical systems with particular focus on methodology for production forecasting and history matching of hydrocarbon reservoirs.
I have a general interest in spatial probability and statistics which originated in post-doctoral research on the use of satellite imagery in mineral exploration. With Allan Seheult, a DTI LINK funded project studied various aspects of a class of spatial Markov chains proposed by Qian and Titterington (JRSS B, 1990). On a consultancy basis, we have also produced a short course on geostatistics.
Like most statisticians, I try to provide statistical help and advice to researchers from other disciplines. Publications have arisen from work with Richard Hall (University of Leeds) on problems arising in hip-joint replacement and with Brian Diffey (Regional Medical Physics Unit) on some dermatological studies.
Other than the main research areas mentioned above, the list below gives some areas of research in statistics in which I would be particularly interested to supervise research students. If any of these are of interest to you, please contact me for more information.
You may also wish to read some more general information about postgraduate study in statistics at Durham