Dr James Salter
Postdoctoral Research Associate
Telephone: 01392 726403
Extension: (Streatham) 6403
I'm currently working with Prof. Gavin Shaddick and others on a World Health Organization project, involved in modelling global ambient air pollution (PM2.5), and the effect this has on various causes of death.
Also involved in a machine learning-based project with a local company, Prof. Richard Everson, and Dr Fabrizio Costa.
Research interests: emulating and history matching (calibrating) expensive computer models with high-dimensional output.
Post-doc, University of Exeter, April 2017 - October 2017
PEN funded project, entitled "Searching for the deglaciation: spatio-temporal boundary condition uncertainty and its implications for understanding abrupt climate change", with Daniel Williamson (Exeter) and Lauren Gregoire (Leeds).
PhD, University of Exeter, September 2013 - March 2017
Title: Uncertainty quantification for spatial field data using expensive computer models: refocussed Bayesian calibration with optimal projection
Supervised by Daniel Williamson
Salter, J. M., & Williamson, D. B. (2018) Efficiently calibrating spatio-temporal computer models. In preparation.
Salter, J. M., Williamson, D. B., Gregoire, L. J., & Edwards T.L. (2018). Quantifying spatio-temporal boundary condition uncertainty for the deglaciation. In submission. Available at https://arxiv.org/abs/1808.09322
Salter, J. M., Williamson, D. B., Scinocca, J., & Kharin, V. (2018). Uncertainty quanti[c]cation for spatio-temporal computer models with calibration-optimal bases. Accepted, Journal of the American Statistical Association. Available at http://arxiv.org/abs/1801.08184
Salter, J. M., & Williamson, D. (2016). A comparison of statistical emulation methodologies for multi-wave calibration of environmental models. Environmetrics, 27(8), 507-523.
Williamson, D., Blaker, A. T., Hampton, C., & Salter, J. (2015). Identifying and removing structural biases in climate models with history matching. Climate Dynamics, 45(5-6), 1299-1324.