Dr Andrew (Andy) Golightly's Home Page

Research interests

My main research interests in no particular order:

  • Multivariate diffusion processes
  • Stochastic kinetic models represented by jump processes
  • Efficient simulation based Bayesian inference (using e.g. MCMC, SMC, pMCMC) for large stochastic models with particular focus on diffusion and jump processes
  • Sampling conditioned jump and diffusion processes
  • Emulation of computer models via Gaussian processes


  • Biennial RSS Research Prize (2009)

Currently funded research projects

  • Assessing the effect of caloric restriction on core temperature and physical activity in mice using stochastic differential equation driven state space models - Ashleigh McLean, CDT funded PhD student (2016-19)
  • Fundamentals of Hamiltonian Monte Carlo for Bayesian inference of phylogenetic trees - Matthew Robinson, EPSRC funded PhD student (2015-18), jointly supervised with Dr Tom Nye and Prof Richard Boys
  • Bayesian calibration of stochastic kinetic models using spatial Dirichlet processes - Aamir Khan, EPSRC funded PhD student (2014-17), jointly supervised with Prof Richard Boys
  • Urban sustainability through Data Analytics - Yingying Lai, SAgE Faculty funded PhD student (2014-18), jointly supervised with Prof Richard Boys and Prof Phil Taylor (Newcastle Institute for Research on Sustainability)

Previous research projects

  • Bayesian inference for stochastic differential mixed-effects models - Gavin Whittaker, PhD student (2011- June 2014, July 2015-2016), jointly supervised with Prof Richard Boys
  • Mathematical models for the developed Neolithic - funded by Leverhulme Trust funded (2009-12), with Dr Graeme Sarson, Prof Anvar Shukurov, Prof Richard Boys, Dr Andrew Baggaley and Dr Daniel Henderson

MMathStat project students:

  • Andrew Robson: Pseudo-marginal MCMC for diffusion processes, 2015
  • Josh Rushton-Crawshaw: Metropolis adjusted Langevin schemes for a linear class of diffusion processes, 2015
  • Matthew Upton: Sequential Monte Carlo schemes for Markov jump processes, 2014
  • Aleksandra Svalova: Bayesian inference for stochastic differential equations with application to finance, 2013
  • Elizabeth Goodall: MCMC for stochastic kinetic models via a linear noise approximation, 2012
  • Lane Stephenson: Bayesian nonparametric regression using Gaussian processes, 2011

Summer project students:

  • Matheus Sebestyen Paiola: Monte Carlo pricing of options, 2015
  • John Duke: Numerical simulation and inference for stochastic differential equation models in systems biology, 2010 (with Prof Richard Boys)
  • Lauren Speight: Approximate Bayesian computation for stochastic kinetic models, 2010 (with Prof Richard Boys)
  • Rochelle Firth and Susanna Roig: Stochastic simulation for systems biology models, 2007 (with Dr Colin Gillespie)

Main duties:

  • RSS local group chair
  • Associate Editor for Mathematical Biosciences
  • Seminar organiser (internal)
  • Personal tutor
  • Statistics postgraduate selector (2014-15)

Dr Andrew Golightly,
School of Mathematics & Statistics
Newcastle University, Newcastle upon Tyne NE1 7RU, UK
Telephone: +44 (0)191 222 7312, Fax: +44 (0)191 222 8020
E-mail: a.golightly at ncl.ac.uk