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Research in Statistical Science covers foundational, computational and theoretical aspects of probability and inferential statistics, as well their intersection with multiple disciplines. It includes, but is not limited to, the following topics:
- Philosophical and mathematical foundations of probability and statistics
- Theory of inference, including Bayesian theory, predictive inference and asymptotic theory
- Statistical methodology for causal inference
- Inference for stochastic models, nonparametric and semiparametric inference
- Computational statistics and machine learning algorithms for estimation and prediction
- Decision analysis via operational research and financial methods
You can find out about the research activity of individual members of the department in the following links:
- Directory of academic and lecturing staff
- Directory of research associates and fellows
- Directory of PhD students
- Research student profiles
Information on our research programme and funding for postgraduate studies can be found in the Prospective Graduates page.
Research Themes
The department's methodological and applied research is organised into six areas. Follow the links for information on research activities, groups and members.
- Causality. This theme addresses the formulation, computation and inference of cause-effect relationships with observational and limited experimental data.
- Computational Statistics and Machine Learning. This theme is concerned with advancing the theory, methodology, algorithmic development and application of computationally intensive approaches to modern statistical inference.
- Economics, Finance and Business. This theme is concerned with the application of statistical, econometric and machine learning methods to problems arising in economics, finance and business.
- Environmental Statistics. Activities under this theme include contributions of statistics & data science to applications in any area of environmental science and engineering.
- Probability. Research in this theme addresses fundamental properties of universal stochastic models, and spans applications in life sciences, mathematical physics, finance, insurance and ergodic theory.
- Statistics in Biomedicine and Health Economics. This theme has a research programme that encompasses both applied health research and the development and evaluation of statistical methods.
Much of this work is interdisciplinary and involves collaborations within and outside UCL. The department is also a member of ELLIS.