Dr David Warne

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Lecturer in Statistical Inference for Complex Models, School of Mathematical Science

David is passionate about the application of data science to solve real world problems. In particular, he investigates mathematical, statistical, and computational techniques for applications that improve our understanding of complex biological and ecological systems.

David’s research also focusses on the development of advanced Monte Carlo sampling schemes for Bayesian inference for challenging stochastic models that frequently arise in biological and ecological settings. With a background in computer science, programming and High Performance Computing (HPC), he is always interested in algorithm implementation for efficient utilisation of modern, massively-parallel, computer hardware.

Research Interest:

  • Mathematical biology and ecology
  • Stochastic modelling
  • Bayesian Inference
  • Monte Carlo methods
  • High performance computing

Society Membership:

  • Australian Mathematical Society
  • Society of Mathematical Biology
  • Statistical Society of Australia


  1. David J. Warne, Ruth E. Baker, Matthew J. Simpson. 2020. A practical guide to pseudo-marginal methods for computational inference in systems biology. Journal of Theoretical Biology, 110255. DOI:10.1016/j.jtbi.2020.110255
  2. David J. Warne, Ruth E. Baker, Matthew J. Simpson. 2019. Using experimental data and information criteria to guide model selection for reaction–diffusion problems in mathematical biology. Bulletin of Mathematical Biology, 81:1760–1804. DOI:10.1007/s11538-019-00589-x
  3. David J. Warne, Ruth E. Baker, Matthew J. Simpson. 2019. Simulation and inference algorithms for stochastic biochemical reaction networks: from basic concepts to state-of-the-art. Journal of the Royal Society Interface, 16(151):20180943. DOI:10.1098/rsif.2018.0943
  4. David J. Warne, Ruth E. Baker, Matthew J. Simpson. 2018. Multilevel rejection sampling for approximate Bayesian computation. Computational Statistics & Data Analysis, 124:71–86. DOI:10.1016/j.csda.2018.02.009
  5. Duzgun Agdas, David J. Warne, Jorge Osio-Norgaard, Forrest J. Masters. 2018. Utility of genetic algorithms for solving large scale construction time/cost trade-off problems. Journal of Computing in Civil Engineering, 32(1):04017072. DOI:10.1061/(ASCE)CP.1943-5487.0000718
  6. David J. Warne, Ruth E. Baker, Matthew J. Simpson. 2017. Optimal quantification of contact inhibition in cell populations. Biophysical Journal, 113(9):1920–1924. DOI:10.1016/j.bpj.2017.09.016
  7. David J. Warne, Neil A. Kelson, Ross F. Hayward. 2014. Comparison of high level FPGA hardware design for solving tri-diagonal linear systems. Procedia Computer Science, 29:95–101. DOI:10.1016/j.procs.2014.05.009
  8. Ferry Melchels, Paul Wiggenhauser, David Warne, Mark D. Barry, Fook Rhu Ong, Woon Shin Chong, Dietmar W. Hutmacher, Jan-Thorsten Schantz. 2011. CAD/CAM-assisted breast reconstruction. Biofabrication, 3(3):034114. DOI:10.1088/1758-5082/3/3/034114

External Links:

    • Google Scholar: https://scholar.google.com.au/citations?user= t8l-kuoAAAAJ&hl=en
    • ORCID: 0000-0002-9225-175X
    • GitHub: https://github.com/davidwarne
    • Twitter: @DavidJWarne
    • e-prints: https://eprints.qut.edu.au/view/person/Warne,_David.type.html