Senior Lecturer
Telephone: (01792) 602580
Room: Cellular Office - 202
Second Floor
Data Science Building
Singleton Campus

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 using computing techniques, such as medical statistics, machine learning (ML)/deep learning(DL), natural language processing (NLP), computational intelligence (artificial neural networks, fuzzy logic, nature-inspired computing etc), predictive analytics and data mining. He is particularly interested in ML (DL) and AI for  electronic health records and –omics data, and creation of innovative methods to extract  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 was recipient of IFIP-WG8.9 “Outstanding Academic Service Award".
  • Dr Zhou was the recipient of “Outstanding Reviewer Award" from Fuzzy Sets and Systems; IEEE Transactions on Cybernetics; Journal of Biomedical Informatics; Journal of Science and Medicine in Sport; Applied Soft Computing, Knowledge Based Systems, Expert Systems with Applications.

Prospective PhD students

Dr Zhou is very interested to supervise strong potential PhD students in the following areas.

1)       Interpretable ML/DL in healthcare

2)       ML and NLP in pharmacovigilance: detecting adverse drug events, drug-drug interactions etc

3)       Data driven approach to identification of patterns of multimorbidity and polypharmacy

4)       ML and NLP for early prediction of chronic conditions

5)       Disease phenotyping from routine electronic healthcare records

6)       Identifying determinants of health outcomes from routine electronic healthcare records

7)       Identification of complex interactions of risk factors in epidemiological data 

8)       Integrative –omics and electronic health records for precise disease understanding.

9)       Biomedical signal/image processing and applications: Physical activity analysis; EEG signals processing; Intelligent digital radiology.

You are welcome to explore any topics of AI/ML/NLP in health data analytics with Dr Zhou.

PhD Studentships

The EPSRC funded PhD studentships are available within the UKRI Centre for Doctoral Training in Artificial Intelligence, Machine Learning & Advanced Computing.  If you are interested in AI/ML/NLP for health data analytics, please contact Dr Zhou.

Areas of Expertise

  • Health informatics
  • Machine learning (ML)/ Deep learning (DL)
  • Artificial intelligence (AI)
  • Big data analytics
  • Epidemiology and public health
  • Text mining and natural language processing (NLP)
  • Medical statistics
  • Data mining and knowledge discovery
  • Fuzzy logic and modeling
  • Biomedical signal processing
  • Information aggregation/integration
  • Computational intelligence


  1. & Harnessing the Power of Machine Learning in Dementia Informatics Research: Issues, Opportunities and Challenges. IEEE Reviews in Biomedical Engineering, 1-1.
  2. & Predictors of objectively measured physical activity in 12‐month‐old infants: A study of linked birth cohort data with electronic health records. Pediatric Obesity, e12512
  3. & Covariate shift estimation based adaptive ensemble learning for handling non-stationarity in motor imagery related EEG-based brain-computer interface. Neurocomputing 343, 154-166.
  4. & Mining electronic health records to identify influential predictors associated with hospital admission of patients with dementia: an artificial intelligence approach. The Lancet 392, S9
  5. & Light source detection for digital images in noisy scenes: a neural network approach. Neural Computing and Applications 28(5), 899-909.

See more...


  • PMIM402 Machine Learning in Healthcare

    Data scientists working in healthcare are called to deal with problems involving classification and pattern recognition. The objective of this module is to provide the essential theory and practical aspects of widely used machine learning software. This is a core/compulsory module of 20 credits. Module leaders are Arron Lacey and Shangming Zhou


  • Unravelling Polypharmacy: Determining interaction patterns between medications using complex electronic health records for better patient care. (current)

    Student name:
    Other supervisor: Dr Shang-Ming Zhou
    Other supervisor: Prof Xianghua Xie
  • Mining free-text clinical notes for early prediction of the progression and recurrence of colorectal cancer. (current)

    Student name:
    Other supervisor: Prof Ronan Lyons
    Other supervisor: Dr Shang-Ming Zhou
  • Development and Evaluation of a Secure Data Portal and Interactive Platform of Disease Phenotyping for Retrieval and Analysis of the Terminologies of Diagnoses, Symptoms, Medications and Procedures in Wales (current)

    Student name:
    Other supervisor: Prof Sinead Brophy
    Other supervisor: Dr Shang-Ming Zhou

External Responsibilities

Research Groups

  • UKRI Centre for Doctoral Training in AI, ML and Adv Comp

    Funded by EPSRC led consortium, the UKRI CDT in Artificial Intelligence, Machine Learning and Advanced Computing provides 4-year, fully funded PhD opportunities across the broad areas of particle physics and astronomy, biological and health, and mathematical and computer sciences. Dr Zhou is the Area Lead, and the Chair of Equality, Diversity and Inclusivity Board

  • Health Data Research UK Wales and Northern Ireland Site

    Funded by MRC led consortium, Health Data Research UK is uniting the UK’s health data to make discoveries that improve people’s lives.

  • National Centre for Population Health and Wellbeing Research

    Funded by Health and Care Research Wales, the NCPHWR aims to improve the health and wellbeing of the people of Wales, and help them live a longer healthier life

  • The Farr Institute @ CIPHER

    Funded by the MRC led consortium, the CIPHER ( Centre for Improvement in Population Health through E-records Research ) is one of the four co-ordinating centres of the Farr Institute, UK. It is a multinational research partnership between academia, the UK national health service (NHS) and industry, focussed on improving the lives of patients and the population through informatics.

  • Patient & Population Health and Informatics (PPHI)

    PPHI is a multidisciplinary research centre of international standing, conducting eHealth and Informatics Research, Health Services Research and Population Health Studies. Its goal is to make a difference to people’s lives by substantially improving their health and the delivery of health services.


    Funded by the MRC led consortium, the DECIPHer (Centre for the Development and Evaluation of Complex Interventions for Public Health Improvement) is one of five UKCRC Public Health Research Centres of Excellence. The centre aims to develop, test, evaluate and implement complex interventions and policies that achieve sustainable improvements in health and wellbeing, and address health inequalities. Our research has a particular focus on the health of children and young people.

  • Welsh Arthritis Research Network (WARN)

    The Welsh Arthritis Research Network (WARN) has been established by the National Institute for Social Care and Health Research and the Welsh Government. It aims to identify arthritis and musculoskeletal research priorities for Wales, raise the profile of arthritis and musculoskeletal research in Wales and ultimately improve the quality of life and care of people living with arthritis in Wales.