Institute for Mathematical Innovation

IMI/SAMBa Thematic Semester on Markov Chain Monte Carlo Methods


September 2016 - January 2017

Markov Chain Monte Carlo (MCMC) is a central method in statistics and computational physics, which is used to solve the problem of sampling from a complicated distribution. In recent years the methodology has also emerged as a hot area of research in engineering, numerical analysis and machine learning.

This academic semester sees two MCMC experts joining IMI. Newly appointed IMI Global Chair, Professor Colin Fox is an expert in MCMC methods for large-scale engineering applications and Professor Nigel Wilding, seconded to IMI from the Department of Physics is an expert in MCMC methods in soft matter physics.

To make the most this unique opportunity to further the use of MCMC in research across campus, IMI and SAMBa are hosting a university-wide thematic semester on these pivotal methods, which will provide a forum for academics from all disciplines to get together to exchange ideas and discuss research areas of common interest.


Recent events

  • 25 November, 12.15pm: Numerical Analysis Seminar by Claudia Schillings (HU Berlin) on “Scaling Limits in Computational Bayesian Inversion”
  • 22 November, 1.15 pm: Statistics Seminar by Chris Jennison (Bath) on "Search and jump algorithm for Markov Chain Monte Carlo sampling” (CB, Room 5.8)
  • 21 November, 1.15 pm: Statistics Seminar by Adam Johansen (Warwick). Title: TBA (CB, Room 3.16)
  • 18 November, 12.15 pm: Numerical Analysis Seminar by Rob Scheichl (Bath) on “Multilevel subset simulation to predict rare events” (4W, Room 1.7)


Programmme Overview


Join the MCMC Group at University of Bath

All academics at the University of Bath interested in MCMC are warmly invited to take part in all or parts of the IMI/SAMBa thematic semester.

To express your interest, please contact Professor Rob Scheichl at 




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MCMC semester will further the use of a sophisticated simulation technique in research across campus, Sep 2016