Yanzhong Wang

Yanzhong Wang

Dr, Head of Medical Statistics (Consultancy and Service),

  • Phone88223
  • 10223

Personal profile

Research interests (short)

  • Epidemiology and prognostication of stroke
  • Patterns and trajectories of multimorbidity 
  • Clinical prediction models
  • Statistical, machine learning and epidemiological methods
  • Clinical trials, large epidemiological studies and health informatics

Biographical details

Yanzhong Wang is Professor of Statistics in Population Health and Head of Medical Statistics (Consultancy and Service) at King’s College London. He obtained his PhD in statistics from University of Glasgow in 2004, and then worked at Cambridge and Glasgow Universities on cancer genomics, large epidemiological studies and clinical trials before joining King’s College London in 2009. His main research interests are clinical prediction models, stroke epidemiology, multimorbidity, and clinical trials. He is a module leader for the Master of Public Health (MPH). He leads high-impact research on epidemiology and prognostication of stroke which was widely reported in Daily Mail, Telegraph, Guardian and Sky News. He is director of statistical consultancy providing statistical advice and support to clinical researchers at Guy's and St Thomas' Hospitals and NIHR Biomedical Research Centre (BRC) at King's. In 2014, he worked as an expert statistician on ‘the Chantler Review’ to advise UK government on legislation on plain packaging of cigarettes. He is a statistical editor/advisor for PLOS Medicine, Thorax and Emergency Medicine Journal (EMJ) and a funding committee member of NIHR doctoral fellowship (DCAF).  

Management roles

  • Director of statistical consultancy and service
  • Joint lead of medical statistics
  • Lead of epidemiology research group

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 1 - No Poverty
  • SDG 3 - Good Health and Well-being
  • SDG 5 - Gender Equality
  • SDG 8 - Decent Work and Economic Growth
  • SDG 10 - Reduced Inequalities
  • SDG 13 - Climate Action
  • SDG 16 - Peace, Justice and Strong Institutions

Education/Academic qualification

Statistics, Doctor of Philosophy, Aspects of learning mixtures, University of Glasgow


  • RA0421 Public health. Hygiene. Preventive Medicine
  • Medical Statistics
  • Epidemiology
  • clinical trials
  • Health informatics
  • Bioinformatics
  • Stroke
  • Cardiovascular diseases


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