Our interest in risk relates to decision making under uncertainty. We're engaged in all aspects of the decision support process from problem structuring through data analysis and model building to recommendations. We work closely with industry, applying methods primarily from statistics, probability and decision analysis, to real world problems.
Our current work
Take a look at some of our most recent research projects:
- Bayesian networks
- Bayes linear methods
- Empirical Bayes methods to support risk analysis
- Project risk
- Reliability growth
Academic staff active in this area may be available to supervise PhDs on the following topics.
Alec has a broad interest in risk analysis. He's worked on the use of multi-criteria tools to capture the multidimensionality of risk in the nuclear sector, and on game theoretic modelling of the problem of scheduling counterterrorist patrols. His current interests include innovative ways to use risk matrices and evaluation of medical diagnostic technologies.
John's interested in statistical and applied probability modelling for support decision making under uncertainty. He enjoys working in both Bayesian and Empirical Bayes methods, and development methods for elicitation as well as data analytics.
- Availability and maintainability modelling with particular interest in big data and reliability
- Condition monitoring, and modelling the economic impact of sensor systems
- Expert judgement
- Statistical analysis and machine learning
- Visualisation of big data
Tim’s interested in decision and risk analysis. He has a keen interest in Bayesian methods and elicitation of expert judgement as well as probability and consequence modelling.
Other staff available for PhD supervision include:
Susan's interested in system dynamics modelling and mixing methods.
Lesley's interested in reliability and risk analysis. She has a keen interest in statistics and expert judgement.