We all Google. You may even have found this talk by Googling. What you may not know is that behind the Google’s and other search engines is beautiful and elegant mathematics. In this talk, I will try to explain the workings of page ranking and search engines using only rusty calculus.
An alternative version of this lecture presented at the University of Calgary is also available.
In the 1940s Alan Turing’s homosexuality was an open secret amongst his co-workers at Bletchley Park. In 1952 the secret became widely known when Turing was arrested on charges of “gross indecency” under the same 1885 law that had led to the imprisonment of Oscar Wilde over half a century earlier. Opting for chemical “treatment” of his “condition” rather than imprisonment, Turing was one of many well-known casualties of a heightened drive against homosexuality in a postwar Britain that drew the line between the normal and the deviant more sharply than ever before. In his talk, Chris Waters will discuss Turing’s sexual proclivities and their meanings in the context of his times, focusing in particular on his arrest and subsequent fate in the context of the sexual politics of the first half of the 1950s. In addition, he will discuss the shaping of Turing’s posthumous reputation, beginning with the attempts made by the Gay Liberation Front in the 1970s to render Turing the gay icon he has become today.
Turing's interest in the possibility of machine intelligence is probably most familiar in the form of the 'Turing Test', a version of which has been instantiated since 1991 as the Loebner Prize in Artificial Intelligence. To this date the Loebner Gold Medal has not been won. But should any future winner of the prize count themselves as having created a computer that thinks? Turing's 1950 Mind paper 'Computing Machinery and Intelligence', gives a sustained defence of the claim that a machine able to pass the test, which Turing called the Imitation Game, would indeed qualify as thinking. This lecture will explain the Turing Test as well as Turing's more general views concerning the prospects for artificial intelligence and examine both the criticisms of the test and Turing's rebuttals
This talk provides an introduction to epidemiological analysis where the distribution of health outcomes and related exposures are measured over both space and time. Developments in this field have been driven by public interest in the effects of environmental pollution, increased availability of data and increases in computing power. These factors, together with recent advances in the field of spatio-temporal statistics, have led to the development of models which can consider relationships between adverse health outcomes and environmental exposures over both time and space simultaneously.
Using illustrative examples, from outbreaks of cholera in London in the 1850s, episodes of smog in the 1950s to present day epidemiological studies, we discuss a variety of issues commonly associated with analyses of this type including modelling auto-correlation, preferential sampling of exposures and ecological bias. The precise choice of statistical model may be based on whether we are explicitly interested in the spatio-temporal pattern of disease incidence, e.g. disease mapping and cluster detection, or whether clustering is a nuisance quantity that we need to acknowledge, e.g. spatio-temporal regression. Throughout we consider the practical implementation of models with specific focus on inference within a Bayesian framework using computational methods such as Markov Chain Monte Carlo and Integrated Nested Laplace Approximations.
The talk also serves as a precursor to a graduate level course on spatio-temporal methods in epidemiology. This course will cover the basic concepts of epidemiology, methods for temporal and spatial analysis and the practical application of such methods using commonly available computer packages. It will have an applied focus with both lectures and practical computer sessions in which participants will be guided through analyses of epidemiological data.
BACKGROUND INFORMATION: The Statistics Department, with the support of the Constance van Eeden Fund, is honoured to host Dr Gavin Shaddick during term 2 2012-13. Dr Shaddick, a Reader in Statistics in the Department of Mathematical Sciences at the University of Bath, has achieved international prominence for his contributions to the theory and application of Bayesian statistics to the areas of spatial epidemiology, environmental health risk and the modelling of spatio-temporal fields of environmental hazards.
Dr Shaddick will begin his visit to the Department, by giving the 2012-13 van Eeden lecture. That lecture will inaugurate a one term special topics graduate course in statistics, which the Department of Statistics is offering next term. It will be given by Dr Shaddick and Dr James Zidek (Statistics, UBC) on the subject of spatial epidemiology. This course, which is aimed primarily at a statistical audience, will provide an introduction to environmental epidemiology and spatio-temporal process modeling, as it applies to the assessment of risk to human health and welfare due to random fields of hazards such as air pollution. Please see the course outline for more information.