| Staff Details | ||||
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| Personal Information | ||
| Name | Wilson, Simon Paul | |
| Main Department | Statistics | |
| College Title | Professor | |
| simon.wilson@tcd.ie | ||
| College Tel | +353 1 896 1759 | |
| Web | http://www.tcd.ie/Statistics/staff/simonwilson.shtml | |
| Fax | +353 1 677 0711 | |
| Biography | |
| Simon Wilson is an associate professor in statistics at the Trinity College Dublin. He was awarded a PhD in stochastic modeling from the George Washington University, Washington, DC, in 1993. His research interests are in applications of Bayesian methods in reliability and other fields of science and engineering. | |
| Representations |
| Details | Date |
| REVIEWING (SINCE 2004) Journal No. of papers reviewed Biostatistics Bone Comput. Stat. Data Anal. IEE Trans. IEEE JSAC IEEE Trans. Image Proc. IEEE Trans. Reliab. Image and Vision Computing J. Risk and Reliability J. Roy. Statist. Soc. B J. Roy. Statist. Soc. C Naval Research Logistics Stat. and Comp. Book proposal reviews |
| Membership of Professional Institutions, Associations, Societies |
| Details | Date From | Date To |
| Fellow of the Royal Statistical Society | 1993 | present |
| Member of Sigma Xi Scientific Research Society | 1994 | present |
| Elected member, International Statistical Institute | 2006 | present |
| Member of the International Society of Bayesian Analysis | 2001 | present |
| Awards and Honours | |
| Award | Date |
| Fellow of Trinity College Dublin | 2002 |
| Languages |
| Language | Skill Reading | Skill Writing | Skill Speaking |
| English | Fluent | Fluent | Fluent |
| Spanish | Fluent | Fluent | Fluent |
| Description of Research Interests |
| Bayesian statistics, reliability theory, software reliability, image processing, multimedia database retrieval, Markov chain Monte Carlo simulation methods |
| Research Interests | |||
| ACCELERATED TEST | ANALYSIS OF VARIANCE | BAYES INFERENCE | BAYESIAN ANALYSIS |
| BAYESIAN COMPUTATION | BAYESIAN INFERENCE | BAYESIAN STATISTICS | Biodiversity |
| Biomathematics, Biometrics | Computer Simulation/Modeling | Computer Storage & Retrieval | Data Analysis |
| Databases, database management, data mining | Fatigue/Fracture | High Performance Computing | High performance computing |
| IMAGE ANALYSIS | IMAGE PROCESSING | IMAGE PROCESSING COMPUTER ASSISTED | IMAGE SEGMENTATION |
| Image Processing | Imaging and Computer Vision | MARKOV CHAIN MONTE CARLO | MARKOV RANDOM FIELD |
| MATHEMATICAL COMPUTING | MATHEMATICAL MODEL | MATHEMATICAL MODELING | MATHEMATICAL MODELLING |
| MATHEMATICAL SIMULATION | MONTE-CARLO ALGORITHM | MONTE-CARLO ALGORITHMS | MONTE-CARLO PROGRAM |
| MONTE-CARLO SIMULATION | MONTE-CARLO SIMULATIONS | Machine Learning in Mulitmedia Information Retrieval | Multimedia |
| Parallel Programming | Parallel Systems | Probability | RELIABILITY |
| RELIABILITY THEORY | Reliability (Engineering) | SOFTWARE | SOFTWARE DEBUGGING |
| SOFTWARE RELIABILITY | SOFTWARE TESTING | Software Engineering | Statistics |
| WARRANTIES | WARRANTY RESERVE |
| Research Projects | |
| Project title | Statistical Methods in ICT Applications |
| Summary | Information and communications technology (ICT) continues to generate data that challenge the state-of-the-art in statistical methodology. These data form “complex data systems”; of large size and/or generated at a high rate, indexed in space and/or time, with complex dependencies between variables that must be accounted for in any meaningful analysis. Often, particularly where control and decision-making are needed, the analysis must be fast. This project aims to (a) advance the state of the art of statistical analysis for complex data systems in ICT applications (b) support on-going efforts to create a centre of expertise in this area with international recognition. The challenges provided by several concrete applications will motivate the work, including: reliability of telecoms networks, road traffic modelling and management and source separation for multi-channel images. |
| Funding Agency | SFI |
| Programme | Principal Investigator |
| Type of Project | |
| Date from | 01/01/2009 |
| Date to | 31/12/2012 |
| Person Months | |
| Project title | Reliability of Complex Telecommunications Networks |
| Summary | Telecommunications networks continue to experience exponential rates of growth in data transmission, and organisations and individuals are relying more and more on these networks to support critical activities. These trends drive the desire for highly reliable networks that suffer minimal service outages. The core research question that in this project is the reliability of a complex network where failure occurs through the dependence or interaction between its components: hardware, software and human. Statistical models for this process form the focus of the research. Recent developments in Bayesian network (BN) models, such as dynamic BNs and inference for BN structure, are going to be used to develop a unified modelling approach that can model relationships between hardware components, sub-system redundancy, the interaction with software bugs and the consequences of human error. Collaboration with Bell Labs in Dublin and New Jersey is providing data and feedback. The novelty in the research is (a) advances in statistical modelling methodology with BNs for these complex networks and (b) on the application side, better prediction of failures in complex networks and how they arise. |
| Funding Agency | IRCSET |
| Programme | Postgraduate Fellowship |
| Type of Project | |
| Date from | 01/10/2008 |
| Date to | 30/09/2011 |
| Person Months | |
| Publications |
| Peer Reviewed |
| Yoon JW, Wilson SP, Mok KH, A highly efficient blocked Gibbs sampler reconstruction of multidimensional NMR spectra, Journal of Machine Learning Research, Workshop & Conference Proceedings, 13th International Conference on Artificial Intelligence and Statistics (AISTATS), Chia Laguna Resort, Sardinia, Italy, 13-15 May 2010, edited by Yee Whye Teh, Mike Titterington , 9, 2010, pp940 - 947 Url TARA - Full Text |
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| Ben Flood, Brett Houlding, Simon P. Wilson, Sergiy Vilkomir., A probability model of system downtime with implications for optimal warranty design , Quality and Reliability Engineering International, 26, (1), 2009, 83 - 96 DOI |
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| S.Wilson, T. Joyce and E. Lisay, Reliability prediction from field return data , Lifetime Data Analysis, 15, (3), 2009, p397-410 DOI |
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| Bahman Honari, John Donovan, Toby Joyce, Simon Wilson, Eamonn Murphy , Stress test optimisation using an integrated production test and reliability fi eld model , Quality and Reliability Engineering International, 2009 Notes: [ Accepted for publication, Quality and Reliability Engineering International.] DOI |
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| Toby Joyce, Bahan Honari, Simon Wilson, John Donovan and Oonagh Gaffney, Models for optimization of production environmental stress testing on electronic circuit packs, International Journal of Reliability, Quality and Safety Engineering, 15, (6), 2008, 555-579 DOI |
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| More Publications>>> | |
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