Particular areas of current activity include statistical genetics and biostatistics, statistical methods in retail financial services, time series, core statistical methodology, classification and data mining, with many interactions and overlaps between these areas of research.

Research groups

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Applied probability and theoretical statistics

Find out more about applied probability and theoretical statistics
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Astrostatistics

Find out more about astrostatistics
Coding

Bayesian statistics and computational methods

Find out more about Bayesian statistics and computational methods

Research groups

Biotechnology or Biology Technology Biotech as Concept 3D Illustration Render

Biostatistics

Find out more about biostatistics

Statistical cyber-security

Find out more about statistical cyber-security
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Statistical learning

Find out more about statistical learning

Research groups

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Statistics in finance

Find out more about statistics in finance

Time series, spatial statistics and signal processing

Find out more about time series, spatial statistics and signal processing
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Statistics in public policy and government

Imperial statisticians have a strong interest in the use and development of novel data science methods in the areas of public policy and government.

Related initiatives

Machine Learning Initiative

Raising the profile of statistical machine learning research at Imperial to a global level and connecting active researchers in statistical machine learning across all departments.

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Mathematics in Medicine

Devoted to researching medical and health-related problems where mathematical and statistical models can make a difference.

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Data Science Institute

The Data Science Institute at Imperial College London aims to enhance Imperial's excellence in data-driven research across its faculties by fulfilling the following objectives

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Contact Us

Statistics section administrator: 

Ettore Miuccio
Huxley Building, Room 627
E-mail Ettore

Address:
Department of Mathematics
180 Queen's Gate
South Kensington Campus
Imperial College London
London SW7 2AZ
United Kingdom

Head of Section

Prof. Almut Veraart
View Almut's Professional Web Page
Find out more about research within the Maths Department