Department of Mathematics & Statistics
Quantitative researcher and statistician specializing in financial risk modelling, copula-based dependence, functional time series, and scalable learning for streaming and high-frequency data. My work combines rigorous statistical theory with applied financial econometrics, focusing on volatility modelling, VaR/ES estimation, conditional portfolio optimization, and dynamic risk prediction.
Quant Risk | Copulas | Statistical Learning | Streaming Data Analytics
Associate Professor of Statistics at Qatar University with more than 15 years of experience across academia, applied research, and industrial R&D, including a former role as Permanent Research Engineer at EDF R&D, Électricité de France, in Paris. My work bridges rigorous statistical theory, computational methodology, and applied quantitative finance, with a focus on scalable methods for complex, high-dimensional, functional, and streaming data.
My research focuses on copula-based dependence modelling, portfolio optimization, VaR/ES estimation with high-frequency predictors, functional volatility modelling, and recursive algorithms for real-time statistical learning. These methods are motivated by applications in financial risk management, credit risk, energy markets, and financial time series. I have published more than 25 journal articles, including work in the Electronic Journal of Statistics, Journal of Multivariate Analysis, Annals of Operations Research, and Annals of the Institute of Statistical Mathematics.
Alongside my research, I have taught a broad range of graduate and undergraduate courses in statistics, probability, time series, regression, statistical learning, and statistical computing. I have also supervised PhD, MSc, and BSc students on topics including functional regression, copula-based classification, volatility modelling, censored survival models, and real-time healthcare monitoring.