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The School of Computing & Data Science was established by the University of Hong Kong on 1 July 2024, comprising the Department of Computer Science, Department of Statistics & Actuarial Science and Department of AI & Data Science.

    Department of Statistics and Actuarial Science, The University of Hong Kong

    Programmes & Admissions

    HKU Department of Statistics and Actuarial Science (SAAS) has a long history of offering study programmes in the fields of Actuarial Science, Decision Analytics, Risk Management and Statistics. The Department currently houses different accredited degree programmes at bachelor and master levels, in addition to MPhil and PhD degree programmes:

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    Undergraduate Programmes

    Undergraduate Programmes

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    Taught Postgraduate Programmes

    Taught Postgraduate Programmes

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    Research Postgraduate Programmes

    Research Postgraduate Programmes
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    Big Data Science

    Research Focus

    Our research can be classified into four main research directions:

    Stochastic & Actuarial Modeling

    Stochastic & Actuarial Modeling

    Statistical Methodologies

    Statistical Methodologies

    Biostatistics & Social Statistics

    Biostatistics & Social Statistics

    Big Data Science

    Big Data Science

    Stochastic & Actuarial Modeling

    The Stochastic and Actuarial Modeling group has major strengths and plays a world leading role in nonlinear time series, time varying conditional variance (GARCH) models, large random matrices, ruin probability, dependent insurance risk.

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    Statistical Methodologies

    The Statistical Methodologies group has major strengths in distribution theory, resampling methods, multivariate analysis, and ranking and selection problems. The Statistical Methodologies group has major strengths in distribution theory, resampling methods, multivariate analysis, and ranking and selection problems.

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    Biostatistics & Social Statistics

    The Biostatistics and Social Statistics group has strengths in DNA forensic, clinical trials, longitudinal data analysis, survival analysis, epidemiology, human genetics and cytogenetics.

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    Big Data Science

    The Big Data Science group focuses on big data analytics, data mining, spatial data analysis, network data models, machine learning (ML) and Al. Extensive collaborations have been established with various government departments and companies in the industries.

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    Research Seminars

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    • FEB 5, 2026
    Weighted Q-learning for optimal dynamic treatment regimes with nonignorable missing covariates by Professor Bo FU
    • FEB 4, 2026
    Large language models in the financial domain by Professor Liwen ZHANG
    • JAN 8, 2026
    Optimal decision rules with policy-relevant guarantees by Professor Mats Julius Stensrud
    Thumbnail of Research Seminars

    All interested are welcome

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    Our Students

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    GALINA Chakheeva
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    GALINA Chakheeva

    Current student, 2025-26 entry

    BStat

    "I am excited to be part of the HKU’s BStat in Statistical Decision Sciences first cohort that perfectly combines my passion for data science with my career aspirations. I chose this program because of its professional core in Decision making, which lies at the heart of modern data science. I'm absolutely fascinated by how data can lead to pragmatic decisions in businesses and technology. I believe this specialization will give me the analytical skills and technical knowledge I need to become a successful data scientist in the future.

    Portrait of XIAO Fanju Sean
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    XIAO Fanju Sean

    2025 BSc(ActuarSc) graduate

    BSc(ActuarSc)

    I am most grateful that HKU gave me the freedom to explore my path with steady support. The actuarial science programme’s structured.

    Portrait of CHAN Kong Wing Sarah
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    CHAN Kong Wing Sarah

    2019 BSc graduate (Major in Decision Analytics)

    Decision Analytics

    It still feels like yesterday when I was pursuing my BSc in Decision Analytics at SAAS. Looking back, the programme was both rigorous and inspiring, equipping me with strong academic foundations, critical thinking skills, and an open mindset that continue to guide me today. I was fortunate to learn from exceptional professors and supportive staff in the department. The capstone project, summer research programme, and overseas exchange opportunities all sparked my passion for technology and data-driven decision-making, which eventually led me to pursue a career as a software engineer in the investment banking and tech industries. I’m deeply grateful and proud to be part of this remarkable family.

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