The conference will take place from the 24-27th July 2018.
A draft programme outline is available here (please note this is subject to change).
|1st November 2017||Registration opening|
|1st May 2018||Grant application closes|
|31st May 2018||Early (reduced fee) registration closes|
|30th June 2018||Registration closes, abstract submission deadline, poster printing deadline|
|24th July 2018||Conference opening|
|27th July 2018||Conference closing|
To average or optimise?
Richard Everson began his academic career in physics, reading Natural Sciences at Cambridge, before studying the signatures of chaotic systems for a PhD in Applied Mathematics at Leeds University. He worked for several years on aspects of data analysis in fluid mechanics and brain imaging at Brown, Yale and Rockefeller universities in America, before returning to Britain and the department of Computer Science in Exeter in 1999. He is now a Professor of Machine Learning with particular interests in pattern recognition and multi-objective optimisation. Randomness, through experimental data and computational random number generators, has been a constant feature throughout his career. He has recently been developing methodology for image recognition via image segmentation in the context of spinal M.R.I. scans, wastewater leak detection using Random Forests and involvement in evolutionary methods.
It’s as easy as counting 1, 2, 3. Or is it?
Ruth King holds the Thomas Bayes' chair of statistics at the University of Edinburgh, and is a member of the executive committee of the National Centre for Statistical Ecology. Before 2015, she was a reader in statistics at the University of St Andrews, where she was part of the Centre for Research into Ecological and Environmental Modelling. Her research interests include Bayesian inference, hidden Markov models, and state-space models. She has worked on a wide range of ecological applications of statistics, and in particular on the analysis of capture-recapture data for the estimation of animal abundance and density. Some of her research interests are described in her book "Bayesian analysis for population ecology", published in 2009.
Pólya urns: a journey in discrete probability
Cécile Mailler completed her Ph.D. "Boolean trees and Pólya's urns: probabilist and combinatorics approaches" in 2013 at the Université de Versailles-St-Quentin. From 2013 to 2016, she was a research assistant as part of the EPSRC project on the "Emergence of condensation in stochastic systems". Since 2016, she has been a Prize Fellow in probability at the University of Bath. Her research focuses on applying probability theory to stochastic models emerging from applications in computer science and statistical physics. Her interests include, in particular, Pólya's urns, reinforced branching processes, preferential attachment models for networks, and random Boolean tree models for satisfiability.
Horses for courses: empirical or mechanistic modelling for spatio-temporal point process data
Peter Diggle was the president of the Royal Statistical Society from 2014-16. He currently holds two concurrent appointments, the first at the Faculty of Health and Medicine at Lancaster University, the second at the Institute of Infection and Global Health at the University of Liverpool. He is also one the founding co-editors of the journal Biostatistics and holds honorary appointments with Johns Hopkins University in Baltimore, Columbia University in New York City and Yale University in New Haven. Motivated by statistical applications in biomedical, clinical and health sciences, Peter’s research interests include spatial statistics, longitudinal data analysis and environmental epidemiology. In 1997 he was awarded the Guy medal in silver by the Royal Statistical Society and in 2004-2008 worked as an EPSRC Senior Research Fellow.
The RSC is an annual conference that is organised by students, for students, and open to PhD students or equivalent in any field relating to probability or statistics. The next conference will take place 24-27th July 2018 at the University of Sheffield.