Dr Rowland Seymour

Dr Rowland Seymour

School of Mathematics
Assistant Professor in Mathematics

Contact details

Address
School of Mathematics
Watson Building
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Seymour is a statistician developing Bayesian methods for applications in social and health sciences. Dr Seymour's current interests include developing statistical prevalence estimation methods for different crime types and applications of Bayesian nonparametric methods.

Dr Seymour is a UKRI Future Leaders Fellow, developing computational statistical methods to tackle modern slavery. He has received funding for his research from the EPSRC, the Home Office, the Nuffield Foundation and the International Justice Mission.

Qualifications

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

Biography

Rowland's PhD was in Bayesian nonparametric methods for stochastic epidemic models. Following the completion of his PhD, Rowland was awarded an EPSRC Doctoral Prize which he used to set up the prevalence and computation group at the University of Nottingham's Rights Lab. He joined the University of Birmingham's School of Mathematics as an Assistant Professor in 2022 and became a UKRI Future Leaders Fellow in 2023.

Teaching

Semester 2

LM Bayesian Inference and Computation

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

Recent publications

Article

Seymour, R, Kypraios, T & O'Neill, P 2022, 'Bayesian nonparametric inference for heterogeneously mixing infectious disease models', Proceedings of the National Academy of Sciences of the United States of America, vol. 119, no. 10, e2118425119. https://doi.org/10.1073/pnas.2118425119

Seymour, RG, Sirl, D, Preston, SP, Dryden, IL, Ellis, MJA, Perrat, B & Goulding, J 2022, 'The Bayesian Spatial Bradley–Terry model: urban deprivation modelling in Tanzania', Journal of the Royal Statistical Society Series C (Applied Statistics), vol. 71, no. 2, pp. 288-308. https://doi.org/10.1111/rssc.12532

Seymour, RG, Kypraios, T, O’Neill, PD & Hagenaars, TJ 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 (Applied Statistics), vol. 70, no. 5, pp. 1323-1343. https://doi.org/10.1111/rssc.12515

Conference contribution

Seymour, R, Sirl, D, Preston, S & Goulding, J 2023, Multi-Level Spatial Comparative Judgement Models To Map Deprivation. in Proceedings of the Joint Statistical Meetings 2023. Zenodo, Joint Statistical Meetings 2023, Toronto, Ontario, Canada, 5/08/23. https://doi.org/10.5281/zenodo.8314257

Other contribution

Ghumra, A (ed.), Acil, N, Barker, J, Baziotis, C, Beltran Hernandez, A, Dai, D, Deakin, J, Dettmer, S, Fentham, D, Fontrodona-Bach, A, Hart-Villamil, R, Jenkins, B, Jia, X, Jones, AM, Morris, A, Murakami, A, Seymour, R, Da Silva Xavier, G, Smith, C, Tashev, S, Turner, J, Uche, EO, Xia, X & Zhong, J 2023, Birmingham Environment for Academic Research: Case studies volume 3. University of Birmingham. https://doi.org/10.25500/epapers.bham.00004303

Review article

Seymour, R & Silverman, B 2023, 'How Can We Estimate Modern Slavery Globally?', Chance, vol. 36, no. 4, pp. 22-29. https://doi.org/10.1080/09332480.2023.2290950

View all publications in research portal