Michael is a lecturer in Public Health and a chartered statistician within the School of Health and Wellbeing. He has a BSc (honours) in Applied Mathematics and Astronomy, an MSc in Applied Statistics, and a PhD in Public Health.

Long standing research interests include using novel record linkage techniques and statistical methods to analyse complex linked data for research purposes across the spectrum of public health. Michael is particularly interested in maternal and child health and his current research focuses on child and adolescent health, neurodevelopmental, and educational outcomes related to childhood chronic conditions, early life factors, neonatal and childhood morbidity and maternal/obstetric factors including exposures in-utero.

“The ability to access and (crucially) link together high quality, centrally held, population-wide, patient-level, administrative data across generations (mother and child), across sectors (health and non-health), and over time is vitally important to health research enabling novel life-course analyses and insight into wider determinants (and outcomes) of health. Data linkage pulls together key real-world information from different sources to build even richer, large-scale,  powerful linked datasets capable of answering complex research questions.”