Michail Chronopoulos

Dr. Michail Chronopoulos is a Senior Lecturer in Actuarial Science and Insurance at the Faculty of Actuarial Science and Insurance (FASI), Bayes Business School (formerly Cass), City, University of London. He also holds an Adjunct Associate Professor position in Management Science at the Norwegian School of Economics (NHH). His academic background includes a PhD in Statistics from University College London, an MSc in Statistics from Western Michigan University, and a BSc in Mathematics from the University of Ioannina, Greece.

His research focuses on quantitative decision-making under uncertainty, with applications in actuarial science, management science, and energy economics. Key areas include real options, risk modelling, operations research, game theory, and mathematical finance. He applies these methods to investment decisions in R&D, infrastructure, cybersecurity, and renewable energy. His recent work involves predictive analytics and signal processing for risk management in 5G cybersecurity (H2020 SPIDER project) and demand-side management.

His publication record includes high-impact articles in journals such as European Journal of Operational Research, IEEE Transactions on Engineering Management, and OR Spectrum, covering topics like optimal scheduling of serial projects, bi-level optimization under competition, and cybersecurity investment frameworks. The body of his work demonstrates a consistent trend toward integrating risk aversion, uncertainty, and strategic interaction in investment models.

• Fellow of the Higher Education Academy, UK (2018)

He supervises PhD students including Zixuan Zhang and Lars Hegnes Sendstad, and has led significant research projects such as the H2020 SPIDER project on econometric models for cybersecurity investment. He has previously been involved in the NRC project in Bergen, Norway, focused on decision-making under uncertainty. His work bridges theoretical modelling with practical policy and industry applications, particularly in energy and digital infrastructure.

He is affiliated with the Faculty of Actuarial Science and Insurance at Bayes Business School and contributes to interdisciplinary research in risk and decision sciences.