Rate My Professor Matthew Schofield

Professor Matthew Schofield serves as Professor and Head of the Department of Mathematics and Statistics at the University of Otago. He obtained his PhD in Mathematics and Statistics from the University of Otago in 2007, submitting a thesis entitled 'Hierarchical Capture-Recapture Models' that was formally recognized by the Division of Sciences as being of exceptional quality. After completing his doctorate, Schofield held a Postdoctoral Fellowship at the Applied Statistics Centre, Columbia University. He subsequently served as an Assistant Professor in the Department of Statistics at the University of Kentucky prior to his current appointment at Otago, where he progressed through positions including Senior Lecturer.

Schofield's academic interests center on Bayesian inference and environmental and ecological statistics, with applications across biological sciences including statistical ecology, environmental and earth sciences, biomechanics, physiology, genetics, and diagnostic testing, particularly for spatio-temporal data. His expertise encompasses data science, statistical modelling, and probability. Notable publications include 'On the reliability of N-mixture models for count data' (Barker, Schofield, Link, and Sauer, Ecology Monographs, 2018), '50-Year-Old Curiosities: Ancillarity and Inference in Capture-Recapture Models' (Schofield and Barker, Statistical Science, 2016), 'Bayesian modelling of marked point processes with incomplete records: volcanic eruptions' (Wang, Schofield, Bebbington, and Kiyosugi, Journal of the American Statistical Association, 2019), 'Rejoinder to "On continuous-time capture-recapture in closed populations"' (Schofield and Barker, Biometrics, 2020), and contributions to 'Estimating Presence and Abundance of Closed Populations' (Seber, 2023). Schofield has supervised numerous PhD, Masters, and Honours students and currently holds the position of Co-Editor for the journal Biometrics from 2023 to 2025. He received the Littlejohn Research Award for excellence in research from the New Zealand Mathematical Society in 2018. His contributions have advanced methods in capture-recapture modelling and ecological abundance estimation, impacting statistical ecology and related fields.