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Sylvia Richardson is an MRC Investigator at the MRC Biostatistics Unit and has held a Research Professorship in the University of Cambridge since 2012. Sylvia was also Director of the Unit from 2012 to 2021.
Before joining the BSU, she held the Chair of Biostatistics in the Department of Epidemiology and Biostatistics at Imperial College London since 2000 and was formerly Directeur de Recherches at the French National Institute for Medical Research INSERM, where she held research positions for 20 years. In 2019, Sylvia was awarded Commander of the Most Excellent Order British Empire (CBE). Sylvia has also been awarded the Guy Medal in Silver from the Royal Statistical Society and a Royal Society Wolfson Research Merit award. She is a Fellow of the Institute of Mathematical Statistics and of the International Society for Bayesian Analysis
Sylvia has worked extensively in many areas of biostatistics research and made important contributions to the statistical modelling of complex biomedical data, in particular from a Bayesian perspective. Her work has contributed to progress in epidemiological understanding and has covered spatial modelling and disease mapping, measurement error problems, mixture and clustering models as well as integrative analysis of observational data from different sources. Her recent research has focused on modelling and analysis of large data problems such as those arising in genomics. She is particularly interested in developing new analytical strategies for integrative and translational genomics, including statistical methodology for risk stratification, discovering disease subtypes, and large scale hierarchical analysis of high dimensional biomedical and multi-omics data.
Since January 2021, Sylvia has been the President of the Royal Statistical Society (RSS), the fifth woman to become president in the Society’s 187-year history. Sylvia also founded and co‐chairs the RSS Covid‐19 Task Force, which engages a network of RSS members.
BSU Research OverviewTo better understand multifactorial diseases such as cancer, diabetes and cardiovascular diseases, and to ultimately better target treatments to individuals, researchers are using new biotechnologies that measure genetic code at extremely high resolution as well as downstream functional mechanisms essential to the maintenance of human health, and study designs that combine extensive questionnaires, genotyping and biobanks. However, the amount and diversity of information collected render their analysis difficult and statisticians are faced with the challenge of developing efficient dimension reduction approaches that can discover important predictors and patterns among a vast array of possibilities. Our programme proposes to develop a range of improved statistical techniques and algorithms for finding important combinations of features in large genetic and genomics datasets that characterise or predict health outcomes and for carrying out integrative analyses to characterise heterogeneous disease processes. The new methods will be accompanied by the development of freely available software and will be used in a number of collaborative projects to improve understanding of the regulation of genes and immunological response, to study gene-environment interactions and to develop biomarker-based prognostic signatures.
- Awarded Commander of the Most Excellent Order British Empire (CBE) (2019)
- Awarded the Degree of Doctor Philosophiae Causa for 2017 by University of Oslo (2017)
- Suffrage Science Award in Maths and Computing (2016)
- Elected Fellow of the Academy of Medical Sciences (2016)
- Awarded Fellow to the Institute of Mathematical Statistics (2015)