Dr Ben Swallow

  • Lecturer (Statistics)

Research interests

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. My recent research has concerned Bayesian parameter inference and identifiability for stochastic mathematical models of systems biology, specifically related to the NF-κB cell singalling system.

In 2015 I completed my PhD in Statistics at the University of St Andrews (supervised by Professors Steve Buckland and Ruth King), developing methods for the analysis of multi-species ecological data. I then spent two years as a postdoc at the University of Bristol, using Bayesian methodologies for parameter estimation and uncertainty quantification in inverse methods applied to atmospheric chemistry.

Research Groups


Publications

List by: Type | Date

Jump to: 2020 | 2019 | 2018 | 2017 | 2016
Number of items: 6.

2020

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

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, (doi: 10.1002/ece3.5702) (Early Online Publication)

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 Fri Aug 14 12:37:43 2020 BST.
Number of items: 6.

Articles

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, (doi: 10.1002/ece3.5702) (Early Online Publication)

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)

Research Reports or Papers

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

This list was generated on Fri Aug 14 12:37:43 2020 BST.

Grants

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’


Teaching

Stochastic Processes (Level 4/5)

Multivariate Methods (Level 4/5)


Additional information

GradStat Fellow of the Royal Statistical Society (RSS)

Associate Fellow of the Higher Education Academy

Meetings Secretary for the Environmental Statistics Section, RSS