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About Claire
Professor Claire Miller is a Professor of Statistics in the School of Mathematics and Statistics at the University of Glasgow. She obtained a first-class honours degree in Mathematics and Statistics from the University of Glasgow in 2003 and completed her PhD there in 2007, with a dissertation entitled 'Univariate and multivariate statistical methodologies for lake ecosystem modelling', supervised by Adrian Bowman and Marian Scott. Joining the academic staff at the University of Glasgow in 2007, she has progressed to her current professorial role. Her career has been marked by significant contributions to statistical methodology, particularly in environmental applications. Miller served as President of the International Environmetrics Society from 2023 to 2025 and was a member of the Young Academy of Scotland at the Royal Society of Edinburgh from 2016 to 2021. She was elected a Member of the International Statistical Institute in 2015.
Claire Miller's research focuses on developing spatiotemporal statistical and data analytics methodologies to address real-world environmental challenges, often in collaboration with multidisciplinary academic, public sector, and industrial partners. Her interests include smoothing techniques, functional data analysis, multivariate methods, data fusion, and the design of monitoring networks. Ongoing projects include the GALLANT programme for data analytics in sustainable solutions, data fusion approaches for water quality and soil moisture, spatiotemporal modelling for groundwater monitoring networks, and river water quality modelling. She has earned notable awards, such as the 2025 Barnett Award from the Royal Statistical Society for outstanding contributions to environmental statistics, the 2018 Abdel El-Shaarawi Early Investigator's Award from the International Environmetrics Society, and co-authorship on the 2018 TIES-Wiley best paper award for Gallacher et al. (2017) in Environmetrics. Key publications encompass 'Global lake thermal regions shift under climate change' in Nature Communications (2020), 'Effects of multiple stressors on cyanobacteria abundance varies with lake type' in Global Change Biology (2018), 'Warped multifidelity Gaussian processes for data fusion of skewed environmental data' in Journal of the Royal Statistical Society: Series C (2025), 'State space functional principal component analysis to identify spatiotemporal patterns in remote sensing lake water quality' in Stochastic Environmental Research and Risk Assessment (2021), and 'Spatially weighted functional clustering of river network data' in Journal of the Royal Statistical Society: Series C (2015). Her work has advanced understanding of ecological responses to environmental changes and improved monitoring strategies worldwide.
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