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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Machine Learning, Learning Theory, High-Dimensional Data Analysis, Optimization.
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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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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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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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