Dr Zhou’s research sits within the College “Patient & Population Health and Informatics (PPHI)"Theme. His scholarly interests focus on health and biomedical informatics: data-driven health-related studies by using computing techniques, such as medical statistics, machine learning, computational intelligence (deep learning, fuzzy logic, nature-inspired computing etc), predictive analytics and data mining. He is particularly interested in intelligent data analytics of electronic health records and –omics data, and creation of innovative methods for extracting personally useful information, such as rules and patterns, concerning lifestyles and health conditions from routine health related data to promote healthier lifestyles and prevent disease.
- Dr Zhou is the Fellow of The Higher Education Academy.
- Dr Zhou sits on the IEEE Systems, Man and Cybernetics (SMC) Technical Committee on Enterprise Information Systems, and International Federation for Information Processing (IFIP) Technical Committee on Information Systems -WG 8.9. He was the recipient of IFIP-WG8.9 “Outstanding Academic Service Award".
- Dr Zhou is the Associate Editor for “Journal of Intelligent & Fuzzy Systems” (ISSN : 1064-1246), and is a member of Editorial Board for “World Journal of Methodology” (ISSN: 1949-8462).
Prospective PhD students
Dr Zhou is very interested to supervise strong potential PhD students in the following areas. If you are interested in pursuing your PhD studies in any of these areas, or other problems in the area of healthcare machine learning and informatics, predictive analytics, mining electronic health records etc., you are welcome to contact Dr Zhou y email at the above address.
1) Machine Learning for Pharmacoepidemiological Surveillance
2) Data mining research on detecting adverse drug events for pharmacovigilance
3) Building evidence-base on multimorbidity and polypharmacy in primary care: Data-driven study
4) Machine learning for disease phenotyping from routine electronic healthcare records
5) Identifying determinants of health outcomes from routine electronic healthcare records
6) Identification of complex interactions of risk factors in epidemiological data
7) Intelligent data analytics for integrative –omics and electronic health records for precise disease understanding.
8) Causal reasoning and modelling in epidemiology and public health.
9) Biomedical signal processing and applications:
- Physical activity and sedentary behaviour analysis;
- EEG signals for charactering state of a patient's health.