The Department of Statistics and Actuarial Science is under the Division of Mathematical and Statistical Science, which is one of the six strategic research divisions in the Faculty of Science at HKU. The Research Division across two departments provides a unified platform for mathematical, statistical and actuarial science research with high international visibility and applications leading to impact. The members work closely at all levels, sharing an undergraduate degree, some appointments and numerous research activities. For more details, please visit the website of the Division of Mathematical and Statistical Science.
Our research can be classified into four main research directions: (See our Research Activities and Research Outputs)
 Research Interests of Individual Staff
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Actuarial statistics; Longevity risk
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Actuarial Science; Dependent Structures; Stochastic Orders; Risk Measures; Optimal Insurance; Extreme Value Theory
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Bioinformatics; Protein Modelling; Forensic Statistics; Monte Carlo Simulation
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Robustness; Longitudinal Data Analysis; DNA Profiling and Forensic Statistics; Statistical Genomics
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Influential observations; Multivariate statistics; Non-Linear Random Model
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Survival Analysis. Biostatistics. Public Health. Analysis of Infectious Diseases.
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Big Data Analytics and Risk Management; Social Media Analytics and Intelligent Marketing; Business/Health Informatics; Knowledge Management and IS Adoption; E-business Strategies and Applications
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Dr. David LEE, BSc(ActuarSc), MPhil HK; PhD British Columbia; ASA
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Copula modelling; extreme value theory; high-dimensional dependence structures; multivariate tail dependence
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Bootstrap; Resampling Methods; Statistical theory: Asymptotics and Applications
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Real option theory and applications; Resource economics; Quantitative trading; Quantum computing, blockchain and smart contracts
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Time Series Analysis; Financial Econometrics; Quantile Regression; High Dimensional Data Analysis; Machine Learning
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Computational statistics; Bayesian inference; Generative model and its inference; Nonlinear dynamic model; Asymptotic analysis
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Statistical inference for massive data, Big Data Analytics, Causal Inference and Mediation Analysis, Mixed Models, Biostatistics
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Random Matrix Theory; Time Series Analysis; High-Dimensional Data Analysis
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Actuarial Science; Financial Mathematics; Insurance Risk Models; Financial Risk Analysis; Enterprise Risk Management
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Insurance risk theory, ruin theory, stochastic process
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Actuarial Science; Errors-in-Variables Regression Models; Monte Carlo Simulations; Robustness Studies and Applications of Asymptotic Theory
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Survival analysis; Nonparametric and Semiparametric Inference; High-dimensional data analysis
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Actuarial Science; Insurance Risk Models; Mathematical Finance
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Random Matrix Theory and High-Dimensional Statistics; Applications to High-Dimensional Regression Models, Factor Models, Network Data Analysis and Time Series Analysis
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AI, Bayesian methods; Big data; Clinical trials; Deep learning; High-dimensional analysis; Machine learning; Survival analysis
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Medical Image Analysis; Machine Learning; Computer Vision; AI in healthcare
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Insurance Risk Modelling; Financial Risk Analysis; Survival Analysis
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Big data analytics; Bayesian methods; Biostatistics; Statistical genetics; Bioinformatics; Public health and biomedical research
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Machine learning, Bayesian non-parametrics, scalable inference.
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Time Series Analysis; Extreme Value Theory; Insurance Risk Modelling; Machine Learning
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Time Series Analysis; Econometrics; Causal Inference
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