Dr Ben Swallow

  • Lecturer (Statistics)

email: Ben.Swallow@glasgow.ac.uk
pronouns: He/him/his

Room 222, School of Mathematics and Statistics, University of Glasgow, University Place, Glasgow, G12 8QQ

ORCID iDhttps://orcid.org/0000-0002-0227-2160

Biography

Personal page with up to date information can be found here

Research interests

My research interests lie mainly in the field of Bayesian statistical inference, particularly Markov chain Monte Carlo (MCMC) methods, data integration and model selection, applied to problems in environmental and biological sciences.

I am interested in modelling stochastic real-world systems using Bayesian statistical approaches.

I have particular interest in modelling data with excessive zeros.

My recent research has concerned Bayesian parameter inference and identifiability for stochastic mathematical models of systems biology and epidemiology.

Research units

Publications

List by: Type | Date

Jump to: 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016
Number of items: 12.

2022

Swallow, B. , Xiang, W. and Panovska-Griffiths, J. (2022) Tracking the national and regional COVID-19 epidemic status in the UK using directed Principal Component Analysis. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, (Accepted for Publication)

Kretzschmar, M. E. et al. (2022) Challenges for modelling interventions for future pandemics. Epidemics, 38, 100546. (doi: 10.1016/j.epidem.2022.100546) (PMCID:PMC8830929)

Swallow, B. et al. (2022) Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 38, 100547. (doi: 10.1016/j.epidem.2022.100547) (PMID:35180542)

2021

Hadley, L., Challenor, P., Dent, C., Isham, V., Mollison, D., Robertson, D. A., Swallow, B. and Webb, C. R. (2021) Challenges on the interaction of models and policy for pandemic control. Epidemics, 37, 100499. (doi: 10.1016/j.epidem.2021.100499) (PMID:34534749) (PMCID:PMC8404384)

Swallow, B. (2021) A review of Applied Hierarchical Modeling in Ecology: Volume 2 by Kéry and Royle. Journal of Agricultural, Biological, and Environmental Statistics, 26(2), pp. 325-327. (doi: 10.1007/s13253-021-00440-8)[Book Review]

Sacchi, G. and Swallow, B. (2021) Toward efficient Bayesian approaches to inference in hierarchical hidden Markov models for inferring animal behavior. Frontiers in Ecology and Evolution, 9, 623731. (doi: 10.3389/fevo.2021.623731)

2020

Abdollahyan, M. et al. (2020) Data Study Group Final Report: Roche. Project Report. Alan Turing Institute. (doi: 10.5281/zenodo.3876989).

2019

Swallow, B. , Buckland, S. T., King, R. and Toms, M. P. (2019) Assessing factors associated with changes in the numbers of birds visiting gardens in winter: are predators partly to blame? Ecology and Evolution, 9(21), pp. 12182-12192. (doi: 10.1002/ece3.5702) (PMID:31832152) (PMCID:PMC6854100)

2018

Jones-Todd, C. M., Swallow, B. , Illian, J. B. and Toms, M. (2018) A spatiotemporal multispecies model of a semicontinuous response. Journal of the Royal Statistical Society: Series C (Applied Statistics), 67(3), pp. 705-722. (doi: 10.1111/rssc.12250)

2017

Swallow, B. , Rigby, M., Rougier, J.C., Manning, A.J., Lunt, M. and O'Doherty, S. (2017) Parametric uncertainty in complex environmental models: a cheap emulation approach for models with high-dimensional output. arXiv, (Submitted)

2016

Swallow, B. , King, R., Buckland, S. T. and Toms, M. P. (2016) Identifying multispecies synchrony in response to environmental covariates. Ecology and Evolution, 6(23), pp. 8515-8525. (doi: 10.1002/ece3.2518) (PMID:28031803) (PMCID:PMC5167035)

Swallow, B. , Buckland, S. T., King, R. and Toms, M. P. (2016) Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: an application to a study of birds visiting gardens in winter. Biometrical Journal, 58(2), pp. 357-371. (doi: 10.1002/bimj.201400081) (PMID:25737026) (PMCID:PMC4964939)

This list was generated on Sun May 22 06:17:14 2022 BST.
Number of items: 12.

Articles

Swallow, B. , Xiang, W. and Panovska-Griffiths, J. (2022) Tracking the national and regional COVID-19 epidemic status in the UK using directed Principal Component Analysis. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, (Accepted for Publication)

Kretzschmar, M. E. et al. (2022) Challenges for modelling interventions for future pandemics. Epidemics, 38, 100546. (doi: 10.1016/j.epidem.2022.100546) (PMCID:PMC8830929)

Swallow, B. et al. (2022) Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling. Epidemics, 38, 100547. (doi: 10.1016/j.epidem.2022.100547) (PMID:35180542)

Hadley, L., Challenor, P., Dent, C., Isham, V., Mollison, D., Robertson, D. A., Swallow, B. and Webb, C. R. (2021) Challenges on the interaction of models and policy for pandemic control. Epidemics, 37, 100499. (doi: 10.1016/j.epidem.2021.100499) (PMID:34534749) (PMCID:PMC8404384)

Sacchi, G. and Swallow, B. (2021) Toward efficient Bayesian approaches to inference in hierarchical hidden Markov models for inferring animal behavior. Frontiers in Ecology and Evolution, 9, 623731. (doi: 10.3389/fevo.2021.623731)

Swallow, B. , Buckland, S. T., King, R. and Toms, M. P. (2019) Assessing factors associated with changes in the numbers of birds visiting gardens in winter: are predators partly to blame? Ecology and Evolution, 9(21), pp. 12182-12192. (doi: 10.1002/ece3.5702) (PMID:31832152) (PMCID:PMC6854100)

Jones-Todd, C. M., Swallow, B. , Illian, J. B. and Toms, M. (2018) A spatiotemporal multispecies model of a semicontinuous response. Journal of the Royal Statistical Society: Series C (Applied Statistics), 67(3), pp. 705-722. (doi: 10.1111/rssc.12250)

Swallow, B. , Rigby, M., Rougier, J.C., Manning, A.J., Lunt, M. and O'Doherty, S. (2017) Parametric uncertainty in complex environmental models: a cheap emulation approach for models with high-dimensional output. arXiv, (Submitted)

Swallow, B. , King, R., Buckland, S. T. and Toms, M. P. (2016) Identifying multispecies synchrony in response to environmental covariates. Ecology and Evolution, 6(23), pp. 8515-8525. (doi: 10.1002/ece3.2518) (PMID:28031803) (PMCID:PMC5167035)

Swallow, B. , Buckland, S. T., King, R. and Toms, M. P. (2016) Bayesian hierarchical modelling of continuous non-negative longitudinal data with a spike at zero: an application to a study of birds visiting gardens in winter. Biometrical Journal, 58(2), pp. 357-371. (doi: 10.1002/bimj.201400081) (PMID:25737026) (PMCID:PMC4964939)

Book Reviews

Swallow, B. (2021) A review of Applied Hierarchical Modeling in Ecology: Volume 2 by Kéry and Royle. Journal of Agricultural, Biological, and Environmental Statistics, 26(2), pp. 325-327. (doi: 10.1007/s13253-021-00440-8)[Book Review]

Research Reports or Papers

Abdollahyan, M. et al. (2020) Data Study Group Final Report: Roche. Project Report. Alan Turing Institute. (doi: 10.5281/zenodo.3876989).

This list was generated on Sun May 22 06:17:14 2022 BST.

Grants

March 2022 - EPSRC Impact Acceleration Fund (£5200) for spatio-temporal visualisation tools

December 2021 - University of Glasgow 'Reinvigorating Research' (£25,000) to work on aspects of inference for zero-inflated data.

December 2021 - Edinburgh Mathematical Society 'Research grant' (£1,000) - to supply computational resources for Approximate Bayesian Computation methods for spatial epidemic models.

March 2017 (Co-I): Jean Goulding Institute (Univeristy of Bristol) for data-intensive research seed corn funding (≈£5000) to cover my salary and travel expenses for a project entitled ‘Supervised learning to support the optimisation of chemical reactions’ working with computational chemists at the Universities of Bristol and York and industry partners.

November 2015 (PI): SECURE research workshop grant with additional matched funding from the Cabot Institute (total £2500) for a workshop entitled ‘Modelling uncertainty from multi-scale data streams in environmental and ecological sciences’

Supervision

2021- : Chenglei Hu - Multivariate extremes

2020- : Megan Laxton - Multiscale animal movement

2020- : Stephen Jun Viello - Bayesian spatio-temporal change of support problems

2018 - : Kannat Na Bangchang - Bayesian variable selection in GWAS

  • Villejo, Stephen Jun
    A Bayesian Spatio-Temporal Model to Test for Stability of Risks for Spatially Misaligned Data

Teaching

Stochastic Processes (Level 4/5)

Multivariate Methods (Level 4/5)

Professional activities & recognition

Grant committees & research advisory boards

  • 2021: UKRI, Future Leaders Fellow Peer Review College
  • 2020: Royal Statistical Society, Annual Conference Board
  • 2021: Royal Statistical Society, Discussion meetings committee

Editorial boards

  • 2021: Journal of Statistical Theory and Practice

Professional & learned societies

  • 2017: Associate Fellow, Higher Education Academy
  • 2012: GradStat Fellow, Royal Statistical Society
  • 2019: Member, International Society for Bayesian Analysis
  • 2011: Member, International Biometric Society

Selected international presentations

  • 2014: International Statistical Ecology Conference (Montpellier)
  • 2016: AGU Fall Meeting (San Francisco)

Additional information

Meetings Secretary for the Environmental Statistics Section/Conference Board member/Discussion Meetings Committe member, RSS

GradStat Fellow of the Royal Statistical Society (RSS)

Associate Fellow of the Higher Education Academy