Dr Rowland Seymour

Dr Rowland Seymour

School of Mathematics
Assistant Professor in Mathematics

Contact details

Telephone
+44 (0) 1214146200
Email
r.g.seymour@bham.ac.uk
View my research portal
Address
School of Mathematics
Watson Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Rowland Seymour in an Assistant Professor in Mathematics. His research interests are in computational statistics and Bayesian nonparametrics. Rowland has developed models for a wide range of applications including human rights abuses and outbreaks of infectious diseases.

Rowland is a member of the Mathematical Biology and Healthcare Group, the Applied and Computational Statistics Group, the Institute of Interdisciplinary Data Science and AI, and the Institute for Global Innovation. Rowland has received funding for his research from ESPRC, the Nuffield Foundation and the International Justice Mission.

Qualifications

  • PhD Mathematics, University of Nottingham, 2020
  • MSc Applied Mathematics, Heriot Watt, 2016
  • BSc (Hons) Mathematics with German, University of Southampton, 2015

Biography

Rowland’s PhD was in Bayesian nonparametric for stochastic epidemic models. Following the completion of his PhD, Rowland was awarded an EPSRC Doctoral Prize to work on comparative judgement models.

He was then appointed a Senior Research Fellow at the University of Nottingham’s Rights Lab, where he led the Prevalence and Computation group.

Rowland developed research projects tackling human rights abuses across the world, including human trafficking in Romania and online child sexual exploitation in the Philippines.

Teaching

  • Bayesian Inference

Postgraduate supervision

Rowland is happy to take enquiries from motivated students interested in a PhD in computational statistics.

Research

Research Themes

  • Bayesian computation
  • Inference for comparative judgement data
  • Modelling human rights abuses
  • Inference for epidemic models

Publications

  • R. G. Seymour,  T. Kypraios, and P. D. O’Neill. 2022. Bayesian nonparametric inference for heterogeneously-mixing infectious disease models. Proceedings of the National Academy of Sciences, 119 (10).
  • R. G. Seymour, D. Sirl, S. Preston, I. L. Dryden, B. Perrat, M. J. A. Ellis, and J. Goulding. 2022. The Bayesian Spatial Bradley–Terry model: Urban deprivation modelling in Tanzania. Journal of the Royal Statistical Society: Series C. 71 (2).
  • R. G. Seymour, T. Kypraios, P. D. O’Neill, and T. Hagenaars. 2021. A Bayesian nonparametric analysis of the 2003 outbreak of highly pathogenic avian influenza in the Netherlands. Journal of the Royal Statistical Society: Series C, 70 (5).

View all publications in research portal