Rate My Professor George Streftaris

Professor George Streftaris serves as Professor of Statistics and Head of Actuarial Mathematics and Statistics in the School of Mathematical and Computer Sciences at Heriot-Watt University. He obtained his PhD in Statistics from the University of Edinburgh, an MSc with Distinction in Statistics and Operational Research from the University of Essex, and a Ptychion (BSc) in Statistics and Actuarial Science from the University of Piraeus, Greece. His professional career at Heriot-Watt University commenced with post-doctoral positions at BioSS and the university from 2001 to 2004, progressed to lecturer and associate professor roles from 2004 to 2019, and culminated in his appointment as full professor in 2019.

Streftaris specializes in Bayesian stochastic modelling, inference, and assessment at the interface of statistics, epidemiology, and actuarial science, with applications in predictive modelling and statistical machine learning for health and morbidity risks, critical illness insurance, and epidemiological processes. He has supervised multiple PhD students and postdoctoral research assistants to completion and currently directs PhD research on Bayesian model assessment in epidemiology, morbidity, and mortality. As principal investigator, he has secured grants including the Centers of Actuarial Excellence Grant from the Society of Actuarial (2019–2023) for predictive modelling of medical morbidity risk related to insurance, SCOR Foundation grant (2022–2024) on COVID-19 impacts on breast cancer deaths, Institute and Faculty of Actuaries ARC project (2016–2022) on longevity and morbidity risk, The Data Lab grant (2017–2018) on machine learning for multi-asset strategies, and an IFoA grant (2012–2014) incorporating uncertainty in critical illness insurance pricing. Key publications encompass 'Assessing the dynamics and impact of COVID-19 vaccination on disease spread: A data-driven approach' (2024, Infectious Disease Modelling), 'Laplace based Bayesian inference for ordinary differential equation models using regularized artificial neural networks' (2023, Statistics & Computing), 'Cause-of-death contributions to declining mortality improvements and life expectancies using cause-specific scenarios' (2023, North American Actuarial Journal), 'Interpretable zero-inflated neural network models for predicting admission counts' (2024, Annals of Actuarial Science), and 'Cancer disparities: Projection, COVID-19, and scenario-based diagnosis delay impact' (2025, PLoS ONE). A Fellow of the Royal Statistical Society and member of the International Society for Bayesian Analysis and Greek Statistical Institute, he contributes as a member of the Board of Examiners for the Institute and Faculty of Actuaries and external examiner for UK and overseas institutes, alongside delivering invited seminars at universities and conferences internationally.