Dr John Paul Gosling
My research interests are in the quantification of uncertainty whether it is due to natural randomness or to a lack of knowledge. My research focuses on two main areas: the elicitation of expert opinion and the design and analysis of computer experiments.
Elicitation is the process of translating someone's beliefs about some uncertain quantities into a form appropriate for use in a statistical analysis. An elicited probability distribution is often used as a prior distribution in Bayesian statistical analyses. Elicitation is therefore an important subject: it has a part to play in every Bayesian application where the data do not make the prior beliefs of the decision maker insignificant. My research in this field is the development of novel methods for eliciting probability distributions and the development of computer-based tools for elicitation (an example of this is The Elicitator).
Complex computer simulators are used widely in scientific research to study and predict the behaviour of complex systems. The run times of computationally-intensive simulators are often such that they are impractical to run the thousands of times as is conventionally required for uncertainty analysis, sensitivity analysis or calibration. In response to this problem, efficient techniques have been developed based on a statistical representation of the simulator. My work in developing these techniques has been to create an efficient input screening algorithm and to produce a statistical method designed to emulate simulators that are dynamically evolving for a fraction of the original computational cost.
Research groups and institutes
Current postgraduate research students
Postgraduate research opportunities
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