I am a Research Associate working under the supervision of Prof. Daniela De Angelis on infectious disease epidemiology by using Bayesian statistical methods. My work focuses on the development of computational methods for the real-time monitoring of infectious diseases such as the CoVID-19 pandemic.

Before taking up my current position I worked as Research Fellow at the University College of London and at the University of Cambridge. I hold a Phd in Statistics from the Athens University of Economics and Business (Greece) where I completed my dissertation on `Bayesian modelling of high-dimensional financial data using latent Gaussian models’. My research interests include statistical inference for high-dimensional stochastic models, computational statistics, machine learning and modelling of biological, economic and financial data.

Recent publications

• Alexopoulos, A., Dellaportas, P., and Forster, J.J. (2019). Bayesian forecasting of mortality rates by using latent Gaussian models. Journal of the Royal Statistical Society: Series A (Statistics in Society), 182(2), 689-711 DOI: https://rss.onlinelibrary.wiley.com/doi/full/10.1111/rssa.12422
• Alexopoulos, A. and Bottolo, L. (2020) Bayesian variable selection for Gaussian copula regression models. Journal of Computational and Graphical Statistics DOI: doi.org/10.1080/10618600.2020.1840997
• Alexopoulos, A., Dellaportas, P., and Papaspiliopoulos, O.  Bayesian prediction of jumps in large panels of financial time series. Bayesian Analysis (to appear)