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Personal Information
College Photo Name Houlding, Brett
Main Department Statistics
College Title Assistant Professor
College Tel  
Originally from Mansfield, UK, I joined Trevelyan College, Durham University, as an undergraduate in 2000. In 2004 I graduated as a Master of Mathematics (MMath I class honours) and enrolled as a PhD student under the supervision of Prof. Frank Coolen. In 2005 I became a Resident Tutor of Trevelyan College and in 2008 I graduated from Durham as a Doctor of Philosophy (PhD). I joined the Center for Telecommunications Value-Chain Research group in Trinity College Dublin as a postdoctoral researcher in May 2008, and then in May 2009 I joined the new STATICA project of Prof. Wilson. In November 2011 I was awarded a 5 year lecturing position in the Discipline of Statistics.
Details Date
Reviewer for following Journals/Conferences: AISTATS; Quality Reliability Engineering International; International Journal of Approximate Reasoning; Journal of Statistical Planning and Inference.
Description of Research Interests
I have many areas of research interest within Statistics and Operations Research, including both application and theoretical development. Recent work has focused on estimating the total numbers of species of different taxa, which has been joint work with Simon Wilson of Trinity College and Mark Costello of the Leigh Marine Laboratory, University of Auckland. Currently this is based on data from the dates of first reporting of different species, starting with the initial work of Linnaeus. This question is important in discussion of species extinction rates and biodiversity. We form part of a global team, including researchers in Canada, France, the United States and Australia, that is evaluating the many different methods of estimating species numbers. Other/General Interests: I have a strong interest in the foundations of statistics, and specifically, normative Bayesian statistical decision theory, with previous work in this area focusing on the generalisation of adaptive utility that permits uncertainty in not only a decision maker's beliefs, but also their preferences. A brief outline of work conducted in this area is summarised: Theories of sequential decision making have been developed to consider coherent decision making strategies over several decision epochs when actual decision outcomes are a priori uncertain. Such theories have many areas of application, e.g., experimental design and policy development, with contributions being made by researchers in mathematics, statistics, economics, philosophy and psychology. Traditionally, all uncertainties are modelled via precise probabilities, and all preferences over decision outcomes via known utilities. It is recognised, however, that indeterminacy may complicate assessment of such probabilities and/or utilities, especially when the decision maker has little or no prior experience within the context of the decision problem under consideration. As such, recent attention has focused on developing decision making algorithms that are able to accommodate imprecise probabilities (where precise values are replaced by intervals) and/or uncertain utilities (where fixed quantities are replaced by random variables). This then allows indeterminacy to be taken into account, generalising classical theories of decision making, and permitting the creation of robust Bayesian methods for within statistical decision theory. However, further implications are the effects these generalisations have on the axiomatic foundations of the theory, and also on traditional decision theory concepts such as value of information and risk aversion. Finally, I also have a growing interest in the use of statistical arguments for policy development.
Research Interests
Biological Modeling Biostatistical methods Criminal Statistics Data Analysis
Decision Sciences Forensic Law Game Theory Operations Research
Optimization Probability RELIABILITY THEORY Risk Factors/Analysis
Signal Processing Signal processing Simulation and modelling transportation networks Statistical and simulation methodologies
Statistics Stochastic Processes Utilities
Publications and Other Research Outputs
Peer Reviewed
Costello M, Wilson SP, Houlding B, More Taxonomists Describing Significantly Fewer Species per Unit Effort May Indicate That Most Species Have Been Discovered, Systematic Biology, 62, (4), 2013, p616 - 624
Mark Costello, Simon P. Wilson and Brett Houlding, Predicting total global species richness using rates of species description and estimates of taxonomic effort, Systematic Biology, 61, (5), 2012, p871 - 883
TARA - Full Text  DOI
B. Houlding, F.P.A. Coolen, Nonparametric Predictive Utility Inference, European Journal of Operational Research, 221, 2012, p222 - 230
TARA - Full Text
Houlding B & Haslett J, Method and System for Scheduling of Events, 2011
More Publications and Other Research Outputs >>>

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Last Updated:24-SEP-2014