TMCF workshop series: Prediction algorithms with a causal interpretation (online event)
Wednesday 06 May 2020
Time: 11:00 - 16:30
Bio
Mark is a Professor of Statistical Epidemiology in the Obesity Institute, Leeds Beckett University. He is also a Fellow of the Alan Turing Institute.
Trained as a mathematical physicist, Mark's driving interest centres on improving our understanding of the observable world through modelling. After his PhD, Mark worked as a Consultant Data Analyst before entering academia and has since fashioned a programme of interdisciplinary research that spans the gap between theoretical and applied data analytics. He focuses on modelling complexity and highlighting and solving common analytical problems in observational research.
Mark's research and teaching interests have converged around the insights and utility of causal inference methods in observational research, especially how causal methods might be integrated with machine learning and AI to better understand and model complex systems.
Research interests
Mark is seeking to understand complex relationships between individuals within their natural environment through the development and application of observational methods, specifically through the integration of causal inference modelling and agent-based modelling. An example domain of this challenge is modelling patterns, causes and consequences of obesity within our society – these approaches were also applied to Covid-19 pandemic.
