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Dr Matt Moores

PDRA on i-Like, the EPSRC funded project "Intractable Likelihood: New Challenges From Modern Applications" with Prof. David Firth, in collaboration with the universities of Bristol, Oxford, and Lancaster. My previous postdoc was also at Warwick, working on "In Situ Nanoparticle Assemblies for Healthcare Diagnostics and Therapy" with Prof. Mark Girolami. I am also the current postoc representative for the Department of Statistics IT committee.


I will be lecturing ST340: Programming for Data Science in the Autumn term, 2017/18 academic year, joint with A/Prof Paul Jenkins. I don't have regular office hours, but I am available to meet with students by appointment.

Research Interests

Bayesian computational methods for intractable likelihoods in large-scale networks. I also work on inverse problems in image analysis and surface-enhanced Raman spectroscopy.

Research Grants

  • "Hierarchical clustering of functional data for Raman spectroscopy," 2015 Award for Postdoctoral Collaboration from the Network on Computational Statistics and Machine Learning (NCSML). £2k, joint with Dr. Kirsten Gracie, University of Strathclyde. We were further awarded the £2k Winton Capital Prize for the best project from the 2015 cohort.


The title of my PhD thesis was "Bayesian Computational Methods for Spatial Analysis of Images." My supervisors were Prof. Kerrie Mengersen in the Mathematical Sciences School and Dr. Fiona Harden in the School of Clinical Sciences, Queensland University of Technology, Australia. Prior to commencing my PhD, I was involved in the Visible Cell project at the Institute for Molecular Bioscience, University of Queensland. I’ve also worked in R&D for various international companies: writing software for editing a 3D wireframe mesh of a human face; a multimedia search engine and a cable TV programme guide using speech recognition; and an electronic medical records database based on the ANSI HL7 standard. My masters project investigated Gaussian mixture distributions of exhaled particles.

My blog.

My profile on LinkedIn.

Recent Research

"Accelerating pseudo-marginal MCMC using Gaussian processes" Drovandi, Moores & Boys (2018) Computational Statistics & Data Analysis 118: 1-17, DOI: 10.1016/j.csda.2017.09.002, QUT ePrints

"Bayesian modelling and quantification of Raman spectroscopy" Moores, Gracie, Carson, Faulds, Graham & Girolami (preprint, 2016) arXiv:1604.07299 [stat.AP]

"Preferential attachment of specific fluorescent dyes and dye labelled DNA sequences in a SERS multiplex" Gracie, Moores, Smith, Harding, Girolami, Graham & Faulds (2016) Analytical Chemistry 88(2): 1147–1153, DOI: 10.1021/acs.analchem.5b02776

"Scalable Bayesian inference for the inverse temperature of a hidden Potts model" Moores, Pettitt & Mengersen (preprint, 2015) arXiv:1503.08066 [stat.CO]

"Pre-processing for approximate Bayesian computation in image analysis" Moores, Drovandi, Mengersen & Robert (2015) Statistics & Computing 25(1): 23-33, arXiv:1403.4359 [stat.CO], DOI: 10.1007/s11222-014-9525-6

"An external field prior for the hidden Potts model, with application to cone-beam computed tomography" Moores, Hargrave, Deegan, Poulsen, Harden & Mengersen (2015) Computational Statistics & Data Analysis 86: 27-41, arXiv:1404.2764 [stat.ME], DOI: 10.1016/j.csda.2014.12.001

My Google Scholar profile

Reviewer profile on Publons

R Packages

bayesImageS: Bayesian methods for image segmentation using a hidden Potts model

serrsBayes: Bayesian modelling of surface-enhanced Raman spectroscopy (NEW on CRAN)

I have also contributed bug fixes and enhancements to mritc, RadOnc, RZigZag, and RcppEigen.

Conference and Workshop Attendance

Please see my conference pages.