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Dr Guangquan Li

Assistant Professor

Department: Mathematics, Physics and Electrical Engineering

EE Guangquan Li Staffprofile 255 (1)I am a Lecturer in Statistics at ϲ. My research interests lie in developing and applying Bayesian methods to analyze data arising from health and social sciences. My current research areas include developing novel spatiotemporal models for forecasting, policy evaluation and surveillance (with applications to disease and crime) and developing clustering techniques for time-dependent data (e.g. clustering time trends of burglary rates in a study region).

After I obtained my degree in Mathematics from Newcastle University in 2004, I moved to Imperial College London to study for a Ph.D. in medical statistics.  My thesis, entitled “Stochastic models for carcinogenesis”, focuses on developing mathematical models for describing the initiation and progression of cancer at the cellular level. My Ph.D. viva took place in May 2008 with a rather unexpected outcome of “passed without corrections” (many thanks to my PhD supervisors Dr. Mark Little and Prof Paolo Vineis). After the submission of the thesis, I spent three interesting months in Japan, working at the Radiation Effects Research Foundation in Hiroshima. There I worked on a collaborative research project on evaluating impacts, due to errors in dose estimations, on risk assessment of the atomic bomb survivors. Since late 2008 (till mid-2013), I had been a research associate back at Imperial College London. I worked on various projects with a number of national and international collaborators. In July 2013, I joined ϲ as a Lecturer in Statistics. I am a fellow of the Royal Statistical Society

  • Glory Atilola Bayesian Modelling and Mapping of Health Outcomes in Space and Time using Complex National Surveys Start Date: 24/02/2020 End Date: 25/03/2022
  • Mark Hancock Mapping the uncertain future of longevity: an ensemble approach for forecasting mortality Start Date: 01/10/2017 End Date: 19/07/2021

  • Statistics PhD April 01 2008
  • Information not provided Royal Statistical Society (RSS) 2013


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