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Dr Guangquan Li

Senior Lecturer

Department: Mathematics, Physics and Electrical Engineering

I am a Lecturer in Statistics at Northumbria University. My research interests lie in developing and applying Bayesian methods to analyze data arising from health and social sciences.

EE Guangquan Li Staffprofile 255 (1)I am a Lecturer in Statistics at Northumbria University. 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 Northumbria University as a Lecturer in Statistics. I am a fellow of the Royal Statistical Society

0191 243 7084


BSc (Hons), DIC and PhD

Research Themes and Scholarly Interests

Bayesian spatiotemporal models
Bayesian computation
Clustering methods
Sequential surveillance

Key Publications

Li, G., Haining, R., Richardson, S. and Best, N., Evaluating the No Cold Calling zones in Peterborough, England: application of a novel statistical method for evaluating neighbourhood policing policies, Environment and Planning A, 2013; 45(8): 2012-2026.

Li, G., Best, N., Hansell, A., Ahmed, I., and Richardson, S. BaySTDetect: Detecting unusual temporal patterns in small area data via Bayesian model choice, Biostatistics, 2012; 13(4): 695- 710.

Haining, R., Li, G., Maheswaran, R., Blangiardo, M., Law, J., Best, N. and Richardson, S. Inference from ecological models: air pollution and stroke using data from Sheffield, England. Spatial and spatio-temporal Epi., 2010 2-3:123-131 (2010).

Little, M.P., Vineis, P. and Li, G., A stochastic carcinogenesis model incorporating multiple types of genomic instability fitted to colon cancer data., Journal Theoret Biol, 2008 254:229-238.

To view my Northumbria Research Link page click here


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