Ed's broad research interest is how applied mathematics and statistics can be used together to solve important real-world problems. His current work in the department of Mathematics is developing new statistical methodology to improve the computational efficiency and accuracy of a model that is used by a financial services company based in Manchester. He is part of the Knowledge Transfer Partnership (KTP) programme.
Ed was previously a Senior Research Associate at Lancaster University (2016-2018) where he worked with atmospheric chemists to implement Gaussian process emulators and carried out global sensitivity analysis, uncertainty analysis and model calibration to improve the accuracy and quantify the uncertainty of atmospheric chemical transport models.
Prior to this Ed was at Arizona State University in the US (2012-2015) where he used field data, models, and hierarchical Bayesian statistics to improve our understanding of how and why multi-annual rates of photosynethesis and soil respiration will change under a future climate of elevated CO2 and warming. He also built a novel model of soil CO2 production and transport at multiple depths and times to test commonly adopted steady-state assumptions, under different environmental and meteorological conditions.