Andy Golightly

Professor (Statistics), Durham University

Useful links

• Durham University staff profile
• Turing Fellow profile
• Publications: Google scholar

Research interests

• Bayesian Statistics
• Computationally intensive inference schemes e.g. MCMC, SMC
• Emulation of computer models via Gaussian processes
• Application to complex stohastic processes such as stochastic differential equations and Markov jump processes

Currently funded research projects

• Modelling and inference of tree pandemics in Great Britain - funded by EPSRC New Horizons (2021-23), with Dr Laura Wadkin, Dr Andrew Baggaley and Dr Nick parker
• Accelerating inference for stochastic kinetic models - Tom Lowe, EPSRC funded PhD student (2017-)
• Scalable sequential inference schemes for complex epidemic models - Sam Whitaker, EPSRC funded PhD student (2019-), jointly supervised with Dr Colin Gillespie

Previous research projects

• Streaming data modelling for realtime monitoring and forecasting, funded by The Alan Turing Institute (2019-21), with Prof. Darren Wilkinson and Dr Sarah Heaps
• Efficient parameter estimation for quantitative systems pharmacology, EPSRC IAA and AstraZenica Ltd. funded (02/19-04/19), with Dr Colin Gillespie
• Variational inference for SDEs - Tom Ryder, CDT funded PhD student (2017-20), jointly supervised with Dr Dennis Prangle
• Accelerating pseudo-marginal Metropolis-Hastings schemes for partially observed Markov process models - Tom Lowe, EPSRC funded PhD student (2017-20), jointly supervised with Dr Colin Gillespie
• 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)
• Bayesian inference for stochastic differential mixed-effects models - Gavin Whitaker, PhD student (2011- June 2014, July 2015-2016), jointly supervised with Prof Richard Boys
• Mathematical models for the developed Neolithic - funded by Leverhulme Trust (2009-12), with Dr Graeme Sarson, Prof Anvar Shukurov, Prof Richard Boys, Dr Andrew Baggaley and Dr Daniel Henderson