Gareth Roberts (statistician)

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Gareth Owen Roberts
Born 1964 (age 49–50)[citation needed]
Fields Markov Chain Monte Carlo (MCMC)
Institutions University of Warwick
University of Lancaster
University of Cambridge
University of Nottingham
University of Oxford
Alma mater Jesus College, Oxford
University of Warwick
Thesis Some boundary hitting problems for diffusion processes (1988)
Doctoral advisor Saul Jacka[1]
Doctoral students Alexandros Beskos
Steve Brooks[1]
Flávio B. Gonçalves
Chris Jewell
Konstantinos Kalogeropoulos
Theodore Kypraios
John Leichty [1]
Omiros Papaspiliopoulos
Notable awards Guy Medal (Bronze, 1997) (Silver, 2008)
Fellow of the Royal Society (2013)
Website
royalsociety.org/people/gareth-roberts
www2.warwick.ac.uk/fac/sci/statistics/staff/academic-research/roberts

Gareth Owen Roberts FRS (b. 1964) is a statistician and applied probabilist. He is Professor of Statistics in the Department of Statistics and Director of the Centre for Research in Statistical Methodology (CRiSM) at the University of Warwick.[2] He is an established authority on the stability of Markov chains, especially applied to Markov Chain Monte Carlo (MCMC) theory methodology for a wide range of latent statistical models with applications in spatial statistics, infectious disease epidemiology and finance.[3]

Education[edit]

Roberts was educated at Jesus College, Oxford, graduating in 1985 in Mathematics [4] and subsequently went on to complete in 1988 a PhD thesis on Some boundary hitting problems for diffusion processes[5] under the supervision of Saul Jacka at the University of Warwick.

Career[edit]

Following his PhD, Roberts held various academic positions at the University of Nottingham, the University of Cambridge and Lancaster University before returning to the University of Warwick.[2]

Honours[edit]

His nomination to the Royal Society read:

"Gareth Roberts is distinguished for his work spanning Applied Probability, Bayesian Statistics and Computational Statistics. He has made fundamental contributions to the theory, methodology and application of Markov Chain Monte Carlo and related methods in Statistics. He has developed crucial convergence and stability theory, constructed a theory of optimal scaling for Metropolis-Hastings algorithms, and has introduced and explored the theory of adaptive MCMC algorithms. He has made pioneering contributions to infinite dimensional simulation problems and inference in stochastic processes. His work has already found practical application in the study of epidemics such as Avian Influenza and Foot and Mouth disease."[7]

References[edit]

External links[edit]