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Moores, Matt T. Dr

Faculty Member

  • Lecturer in Statistical Science - School of Mathematics and Applied Statistics 2018 -

Overview


I moved to the University of Wollongong in 2018 to take up a continuing lectureship. Previously, I was a Research Fellow in the Department of Statistics at the University of Warwick. There, I worked on the EPSRC-funded projects i-like: "Intractable Likelihood - New Challenges from Modern Applications" and "in situ Nanoparticle Assemblies for Medical Diagnostics and Therapy." I completed my PhD in 2015, under the supervision of Prof. Kerrie Mengersen and Dr Fiona Harden at Queensland University of Technology (QUT), Brisbane, Australia. My thesis topic was "Bayesian computational methods for spatial analysis of images." Before commencing my PhD, I was involved in the Visible Cell project at the Institute for Molecular Bioscience (IMB), University of Queensland. I also have extensive industry experience, having worked in R&D for international companies such as Oracle, Digital (DEC), and Compaq.

Professional Activities:

Fellow of the Royal Statistical Society (RSS)
Member of the International Society for Bayesian Analysis (ISBA)
Member of the IEEE Signal Processing Society

Awards:

2016 Winton Capital Prize for the best final project report from the 2015 NCSML Awards
2015 Award for Postdoctoral Collaboration from the EPSRC Network for Computational Statistics & Machine Learning (NCSML)

Top Publications


Research Overview


  • Bayesian inference and scalable computation for emerging applications in hyperspectral imaging, such as Raman spectroscopy and satellite remote sensing.

Available as Research Supervisor

Available as Research Supervisor

Potential Supervision Topics


  • Bayesian modelling of spectroscopy
    • Mars 2020 rover
    • riometry of the aurora borealis
    • X-ray spectroscopic CT scans
    • 2D and 3D Raman maps
    • AVIRIS, EO-1 Hyperion & HyspIRI
    Sequential Monte Carlo and MCMC algorithms
    • parallel and distributed computation
    • divide-and-conquer SMC
    • conditionally-singular likelihood and model degeneracy
    • approximate Bayesian computation (ABC)

Top Publications


Research Overview


  • Bayesian inference and scalable computation for emerging applications in hyperspectral imaging, such as Raman spectroscopy and satellite remote sensing.

Potential Supervision Topics


  • Bayesian modelling of spectroscopy
    • Mars 2020 rover
    • riometry of the aurora borealis
    • X-ray spectroscopic CT scans
    • 2D and 3D Raman maps
    • AVIRIS, EO-1 Hyperion & HyspIRI
    Sequential Monte Carlo and MCMC algorithms
    • parallel and distributed computation
    • divide-and-conquer SMC
    • conditionally-singular likelihood and model degeneracy
    • approximate Bayesian computation (ABC)
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Research Areas