The Applied Statistics & Risk Unit (AS&RU) has a remit to encourage and co-ordinate external partnerships which enable the early applications of theoretical, methodological and algorithmic developments.
We have collaborated on producing two catalogues - one on decision support tools (here)Link opens in a new window and another on visualising uncertainty (here)Link opens in a new window
If you would like to discuss potential collaborations, click the 'page contact' link at the bottom of the page.
Professor Jim Q. Smith
Jim is an expert in Bayesian decision analysis, graphical models especially dynamic ones and causal discovery in novel settings. He is a Fellow of the Turing Institute and has an enduring interest in modelling complex and high dimensional domains including the elicitation of expert judgments. He has worked closely with industry and government including forecasting in multivariate settings, statistical application in forensic science, the retrieval of evidence from partial fingerprints, designing decision support systems for volume crime and the prevention of serious crime. He has also worked in product and food safety and statsitical models of public health. Jim Q Smith HomepageLink opens in a new window
Dr Martine J Barons
Director of the Applied Statistics and Risk Unit
Martine has a personal research interest in statistical and mathematical modelling of human systems, decision support, Bayesian networks, structured expert judgement elicitation, risk & uncertainty, survival and other health outcomes.
Martine has a background in mathematics and complex systems and also accountancy & business administration.
Dr Jeremie Houssineau
Jeremie's research interest is in alternative representations of uncertainty, with a particular focus on complex systems. He has also worked on Bayesian statistics, Monte Carlo methods and spatial point processes.
Jeremie has a background in mathematical and statistical modelling and in signal processing, with experience both in industry and in academia.
QED Food Security group
Quantitative, Evidence-Based Decision support for Food Security
This expanding group has a growing reputation for its almost unique use of advanced quantitative methods in tackling the knotty problem of household food security.
Funded by EPSRC, Jim Q. SmithLink opens in a new window & Martine J. BaronsLink opens in a new window established new methods for integrating probabilistic models for decision support, called integrating Decision Support Systems (IDSS), with valuable contributions by Manuele Leonelli. In collaboration with local government, these new methods are being used to underpin bespoke IDSS for policymakers concerned with the reduction of household food poverty in the current changing and increasingly challenging environment.
Sophia K. WrightLink opens in a new window and Jim Q. Smith are working on robustness of decision support models and Rachel L. WilkersonLink opens in a new window and Jim Q. Smith are working on causality in decision support models.
Martine J. Barons & Jim Q. Smith have been appointed by the European Food Standards Agency to provide training in the structured elicitation of expert judgement.
This group has established a large number of collaborations over a range of universities and centres both in the UK and worldwide. It is also intimately connected to the university-wide Food GRPLink opens in a new window (Jim Q. Smith is an academic lead) and works across disciplines in research, teaching and grant applications.
Medical, disease & biology group
Professor Jane L. HuttonLink opens in a new window is an expert in medical statistics, with special interests in survival analysis, meta-analysis and missing data. She has major collaborations in cerebral palsy and epilepsy and is frequently called upon to be a statistical expert witness in court cases. Dr Linda NicholsLink opens in a new window assists in this work.
Dr Simon SpencerLink opens in a new window is an expert in Bayesian inference applied to epidemiology, outbreak detection and source attribution methods, stochastic epidemic models, statistics for analytical science and network inference and validation.
Dr Julia BrettschneiderLink opens in a new window is an expert in statistical methodology for genomic data (e.g. gene expression profiles, microscopic images), quality assessment for high-dimensional data (e.g. microarrays, additive layer manufacturing), Spatial modelling and modelling decision-making processes involving genomic cancer recurrence risk.
Emergency decision support group
Professor Jim Q. Smith has a long history of advising the nuclear industry concerning emergency countermeasures that properly take account of uncertainties in forecasting contamination and also in the study of effective communication of command and control strategies to ground forces that maximise thier rationality.
He is an expert in the design of decision support systems and their use in emergency situations, Bayesian decision making under conflict, methods for combining expert judgments and elicitation, the calculation and communication of risk to stakeholders across the public and private sectors, often in contexts that relate to the environment, energy, food safety and the nuclear industry.