I joined the University of Warwick in 2017 as a Lola-funded Research Fellow in the Mathematics Institute and Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research (SBIDER). My research interests lie mainly in the field of Bayesian statistical inference, particularly Markov chain Monte Carlo (MCMC) methods, data integration and model selection. Working with Professor David Rand, my current research focuses on Bayesian parameter inference and identifiability for stochastic mathematical models of systems biology, specifically related to the NF-κB 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.
I am also a GradStat Fellow of the Royal Statistical Society, and member of the International Biometric Society and International Society for Bayesian Analysis.
2017- Research Fellow, University of Warwick
2015-2017 PDRA, University of Bristol
2011-2015 PhD Statistics, University of St Andrews
2010-2011 MSc Statistics (distinction), University of St Andrews
2006-2010 BA French and Mathematics, Kings College London/ERASMUS Université Paris-Sorbonne (Paris IV)
I have conducted both undergraduate and postgraduate teaching and supervision throughout my academic career to date, and recently supervised two BSc final year projects – one as a co-supervisor and the other as a lead supervisor. My undergraduate teaching has included generating material for technology-enhanced learning, such as:
Additionally, I was awarded Associate Fellowship (AF) of the Higher Education Academy in July 2017.
- Jones-Todd, C. M., Swallow, B., Illian, J. B. and Toms, M. P. (2017) ‘A spatio-temporal multi-species model of a semi-continuous response.’ (JRSS(C), in press)
- Swallow, B., King, R., Buckland, S. T. and Toms, M. P. (2016) ‘Identifying multi-species synchrony in response to environmental covariates.’ (Ecology and Evolution, 6(23), 8515–8525)
- Swallow, B., Buckland, S. T., King, R. and Toms, M. P. (2015) ‘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), 357–371) and press release from BTO.
- 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 applied to greenhouse gas emissions estimation.’ arxiv.org/1702.03696
- Swallow, B., Rigby, M., Rougier, J.C., Manning, A.J., Lunt, M. and O’Doherty S. ‘Dimension-reduction emulation of complex environmental models, with an application to greenhouse gas emissions estimation.’ (In revision)
- Swallow, B., Buckland, S. T., King, R. and Toms, M. P. ‘Assessing factors associated with changes in the numbers of birds visiting gardens in winter: are predators partly to blame?’
- March 2017 (Co-I): Jean Goulding Institute 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’
'Modelling data from multi-scale data streams in ecological and environmental sciences', (University of Bristol, September 2016)
- 'Hierarchical Bayesian models for quantifying uncertainties in complex atmospheric trace gas inversions' (Invited seminar, University of York, July 2017)
- ‘Emulation of a complex high-dimensional atmospheric model’ (Past Earth Network Workshop on Gaussian Process Emulators, University of Leeds, June 2017)
- ‘Bayesian hierarchical modelling of environmental processes’ (Invited talk at Data Intensive Research: Challenges and Opportunities for the GW4 Alliance, University of Exeter, May 2017)
- ‘Studies on drivers of population change in some UK garden birds’ (Invited 'Workshop in Ecology and Behaviour (WEB)' seminar, University of Bristol, February 2017)
- ‘Understanding the effect of parameter uncertainty in complex atmospheric models on estimates of greenhouse gas emissions’ (Chemistry PDRA symposium, University of Bristol, February 2017)
- ‘Accounting for parameter uncertainty in complex atmospheric models, with an application to greenhouse gas emissions evaluation’ (AGU Fall Meeting, San Fransisco, December 2016)
- 'Uncertainty quantification in flux inversions’ (NASA OCO-2 Uncertainty Quantification group telecon, June 2016)
- ‘Using the reversible jump algorithm to determine multi-species synchrony in response to environmental covariates’ (Inaugural Maths Research Day, University of St Andrews, January 2015)
- 'Modelling zero-inflated continuous data: with applications to changes in the number of birds visiting gardens in winter' (International Statistical Ecology Conference, Montpellier SupAgro, July 2014) Awarded best student talk prize.
- 'Sparrowhawks and a decline in sparrows: is there a link?' (4th Channel Network Conference, University of St Andrews, July 2013)
- ‘Bayesian hierarchical modelling of non-negative continuous data with a spike at zero: with an application to garden bird survey data’ (National Centre for Statistical Ecology summer meeting, CEFAS, Suffolk, July 2013)
- 'Coincidental bird irruptions' (Iinternational Statistical Ecology Conference, Oslo, July 2012)
Other academic responsibilities
- Chemometrics and Intelligent Laboratory Systems (awarded Outstanding Reviewer status November 2016)
- Proceedings of the Royal Society A
- Biology Letters.
Research blog contributions