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Research: Background and Interests
Research: Background and Interests
Background
I completed a degree in pure and applied mathematics at Queen's University Belfast in June 1994. After that I went on to do a PhD in theoretical atomic physics (thesis title: 'Multiphoton processes in complex atoms and ions') in the Department of Applied Mathematics and Theoretical Physics at Queen's, completing it in December 1997. I continued to work in atomic and molecular physics as a research fellow at Queen's until September 2000, at which point I moved to the University of Ulster. While doing research in physics, I also did an MA in philosophy which has turned out to be relevant for my subsequent research. For details of some of my physics publications see here.
Current Research
At present I am a lecturer of the School of Computing and Mathematics and a member of the Computer Science Research Institute at the University of Ulster. My research concentrates on the use of probability to understand notions such as explanation (including inference to the best explanation), coherence and confirmation. This work lies at the intersection between artificial intelligence (more specifically reasoning under uncertainty and knowledge discovery) and philosophy of science (and the growing field of formal epistemology). Not all my work in these areas is based on probability theory, however. I have also done some work on inconsistency in knowledge bases and confirmation in a fuzzy context. For papers on these topics and applications see here.
I'm also interested in other topics such as interpretations of quantum mechanics, the philosophy of artificial intelligence and the philosophy of religion. A particular interest is how formal approaches can be applied to traditional arguments such as the design argument. A few papers can be found here.
Below you will find some of my presentations which will give you a flavour of my research interests.
Bayesian Networks
Bayesian
Networks 1, Bayesian Networks 2
- lectures presented at a summer school on 'Causality, Uncertainty and
Ignorance' at the University of Konstanz in August 2004. They provide
an overview of some important aspects of Bayesian networks including
their representation of conditional independence, inference and a
little bit on learning networks from data.
Probability,
Causality and Bayesian Networks
- a seminar at the University of Ulster in March 2007. It has quite a
bit of overlap with the above lectures but relates it more to
probabilistic causality.
Coherence and Inference to the Best Explanation (IBE)
Coherence
measures and IBE
- a talk at a workshop on 'Coherence and Truth' at the University of
Lund in March 2006. How should 'best' be understood in IBE? This talk
looks at coherence measures and shows how one of them might provide a
suitable account of 'best'. The relationship between IBE and
Bayesianism is also considered briefly.
IBE: a
comparison of approaches
- a talk at the AISB'09 symposium on 'Computing and Philosophy' at
Heriot-Watt University in Edinburgh in April 2009. This talk is related
to the last one since it compares a number of different ways of
defining 'best' in IBE using computer simulations. The results seem to
vindicate the coherence measure considered in the previous talk.
Explaining Away
Can Evidence
for Design be Explained Away? Handout with formal results
- a talk at the conference on Formal
Methods in Epistemology of Religion at the Katholieke Universiteit
Leuven, Belgium in June 2009. This talk defines 'explaining away'
formally and identifies conditions under which it occurs. This approach
is applied to design arguments in biology and fine-tuning, but the
formal results might be of interest even if you don't agree with my
conclusions.