Welcome Prospective PhD Students
Shangming is interested in supervising strong potential UK and international PhD students from allied health professionals or computing science backgrounds. The areas of PhD studies include health data science, health and biomedical informatics, artificial intelligience (AI) for healthcare and medicine, quantitative data analysis and/or evaluation of e-health technologies, such as 

• AI in health and care;
• explainable machine learning (XAI) in healthcare; 
•  ethical AI in healthcare;
• electronic health records analytics;
•  natural language processing /text mining in healthcare;
• e-health technology transformation;
• early detection and diagnosis;
• multimorbidity and polypharmacy; 
• disease phenotyping; 
• patient safety;
• etc. 

If you have an ambition in pursuing a PhD study in any related topic, you are most welcome to contact him via the email.

About
Currently, Shangming is the Deputy Director of the Centre for Health Technology at the Faculty of Health: Medicine, Dentistry and Human Sciences. He is also the Director of NHS Kernow Datalab, and an affiliated investigator with the Health Data Research UK(HDR UK). His research was funded by HDRUK, MRC, EPSRC, HCRW, Charities, and international collaborations. Before joining the University of Plymouth, Shangming worked with the Scottish Digital Health and Care Institute and University of Strathclyde, Swansea University, De Montford University, University of Essex, and Chinese Academy of Sciences.

His primary scholarly interests are AI in health and biomedical informatics, health data science, biomedical statistics and information aggregation / integration via type-1 OWA operators and type-2 OWA operators. In implementation science, he is particularly interested in (big) data analytics and AI with electronic health data for personalised medicine, disease phenotyping, polypharmacy, multimorbidity, risk factors identification etc; clinical decision supports driven by type-1 OWA operators and type-2 OWA operators; machine learning and data mining applied to epidemiology and public health. In developmental domains, he is particularly interested in developing and using explainable/transparent machine learning (i.e. XAI), type-1/ type-2 OWA operators and other AI technologies for electronic health records and –omics data to extract personally useful information, such as rules and patterns, concerning lifestyles and health conditions to promote healthier lifestyles and prevent disease.
The medical conditions to which he is particularly interested in applying AI and biomedical statistics techniques include, but are not limited to, the long-term health conditions (such as cancer, dementia, epilepsy, asthma, diabetes, multiple sclerosis, mental health conditions etc.)

His areas of expertise:

•  Artificial intelligence in health & care 
•  Machine learning /deep learning for health data analytics
• Health informatics
• Explainable AI
• Epidemiology
• Population health
• Big data analytics
• Medical statistics
• Data linkage (of electronic health records)
•  Information aggregation/integration 
• Biomedical signal processing
• Data mining and knowledge discovery
• Computational intelligence

He was the recipient of “ Best Paper Award ” sponsored by Springer Nature at the International Conference on Frontiers of Intelligent Computing: Theory and Applications; “ Best Poster Priz e” at the Royal College of Physicians (RCP) Annual Conference; IFIP-WG8.9 “ Outstanding Academic Service Award "; and “ Outstanding Reviewer Award " from Journal of Biomedical Informatics; Journal of Science and Medicine in Sport; Fuzzy Sets and Systems; IEEE Transactions on Cybernetics; Applied Soft Computing, Knowledge Based Systems, Expert Systems with Applications, respectively.

• Fellow of the Higher Education Academy
• Member of IEEE (The Institute of Electrical and Electronics Engineers)
• Member of IEEE Engineering in Medicine & Biology Society
• Member of IEEE Computational Intelligence Society
• Member of IEEE Systems, Man and Cybernetics Society

Editorship

• Scientific Reports (Editorial Board Member)
• Frontiers in Artificial Intelligence (Associate Editor)
• Frontiers in Neurology (Editorial Board Member)
• Frontiers in Network Physiology (Editorial Board Member) 
• Journal of Personalized Medicine (Editorial Board Member) 
• Diagnostics (Editorial Board Member) 
• American Journal of Health Research (Editorial Board Member)
• Transactions on Engineering and Computer Science (Editorial Board Member) 
• IEEE Transactions on Industrial Informatics (Guest Editor) 
• Information Systems Frontiers (Guest Editor) 

Member of Technical Committee for Professional Organisations

• IEEE Computational Intelligence Society Task Force on Explainable Fuzzy Systems
• IEEE Computational Intelligence Society AI in Healthcare Task Force under the Government and Industrial Activities Committee.
• IEEE Systems, Man and Cybernetics Society Technical Committee on Enterprise Information Systems
• International Federation for Information Processing (IFIP) Technical Committee on Information Systems -WG 8.9 (Enterprise Information Systems) 

Member of Program Committees for International Conferences Shangming has served as the invited member of Program Committees for over 110 international conferences.

Current special issues/collections edited:

• Collection – “Polypharmacy in the Over 60s”, Scientific Reports (Editors: Wegdan Bani-issa, Pankaj Bhardwaj, Shang-Ming Zhou)

• Special Issue – “The Future of Diagnostics: Exploring the Role of Artificial Intelligence in Medicine”, Diagnostics (Editors: Shang-Ming Zhou, Yi Guo, Neil Vaughan, Jiaxiang Zhang)

• Special Issue – “Promoting Human Health and Healthcare with Artificial Intelligence and Machine Learning”, Applied Sciences (Editors: Hossein Ahmadi, Sheena Asthana, Shang-Ming Zhou)

PhD Students

• Sherif Shazly (2023~2025)‒ “Machine learning-based prediction of endometrial cancer prognosis” (Director of Study) .
• Xu Wang (2022~2025) ‒ “Improving Medication Verification for Cancer Patients: An AI Led Population Health Study” (Director of Study) .
• Xiatian Fan  (2023~2027) ‒ “Mining Routinely Collected Electronic Health Records to Identify Effective Dietetic Factors for Optimal Care in General Practice” (Director of Study) .
• Tristan Coombe (2023~2029) ‒ “On the Use of Artificial Intelligence in Nursing Education” (Director of Study) .
• Joan Jonathan Mnyambo (2023~2027) ‒“Prediction of Diagnostic Accuracy using Artificial Intelligence and Big Data Analytics from HeroRats for Tuberculosis Detection” (Second Supervisor) 

• Machine Learning for Healthcare 
• Health Data Analytics
• Health Statitics
• Health Informatics & Digital Health
• Research Methods and Ethics

Grants Contracts:

Dr Zhou has received research funding from different sources, including:

• “AI and dental service provision rapid evidence assessment” (General Dental Council)
• “SPHERE: Systems and People-Centric Innovation in Healthcare Redesign” (NIHR & EPSRC)
• “Mining Routinely Collected Electronic Health Records to Identify Effective Dietetic Factors for Optimal Care in General Practice” (FoH PhD Studentship)
• “Older people with intellectual disabilities and epilepsy – recognising and correcting anticholinergic inducing polypharmacy” (Baily Thomas Fund)
• "Early recognition and Assessment of Severely Ill babiEs by paRents – EASIER study" (The Lullaby Trust).
• "Using machine learning to predict subclone evolution and response during chemotherapy" (Health & Care Research Wales)
•  "Improving Medication Verification for Cancer Patients: A Pragmatic AI Driven Population Health Study" (Faculty International PhD Studentship) 
• "Mobilising the use of health data science into chemotherapy for cancer patients" (Higher Education Innovation Fund) 
• "Feasibility Study - Artificial Intelligence Applied to Enhance the Safe and Effective Use of Medicines in Patients with Cancer" (Above & Beyond).
•  "AccelerateAI – Accelerating AI research with General Purpose Graphics Processing Units" (Ser Cymru Capacity Building Accelerator Award ).
• "UKRI Centre for Doctoral Training in Artificial Intelligence, Machine Learning and Advanced Computing" (EPSRC).
• "Health Data Research UK Wales and Northern Ireland Site" (MRC).
• "National Centre for Population Health and Wellbeing Research" (Health and Care Research Wales).
• "MytHICAL-Mental Health Informatics in Children, Adolescents and Young Adults: How Do my feelings become numbers?"(MRC).
• "Study on Big Data Mining Analysis Technologies and the ASEAN Countries' Social, Economic, and Health Relations" (Guangxi University) 
• "Novel machine learning and text mining techniques for accurate disease phenotyping from SNOMED derived clinical texts" (European Convergence Programme)

External Examiner of Postgraduate Programmes:

• MSc Intelligent Systems, De Montfort University, UK
• MSc Business Intelligence and Data Mining, De Montfort University, UK
• MSc Intelligent Systems and Robotics, De Montfort University, UK
• MSc Data Analytics, De Montfort University, UK

External Examiner of PhD Theses and Viva

• University of Canberra, Australia.
• University of Manchester, UK.
• Ulster University, UK.
• De Montfort University, UK.

Invited Lectures:

• “Empowering Digital Health with Advanced Analytics : Type-1 OWA Operators for Aggregating Uncertain Information from Multiple Sources in Integrated Diagnoses.” The International Conference on Digital Health and Telemedicine 19th - 20th October 2023 (Keynote speaker). 
• “UoP-Torbay Health Technology Showcase”, Torbay and South Devon NHS Foundation Trust, University of Plymouth, 23 May 2022.
• “Aggregating Uncertain Information from Multiple Sources for Integrated Diagnoses”, School of Engineering, Computing and Mathematics, University of Plymouth, 18 May 2022.
• “Artificial Intelligence in Health and Care: Promises and Challenges”, Faculty of Health, University of Plymouth, 14 September 2021.
• “Do AI and Machine Learning Approaches Provide an Opportunity for Preventative Health and Are the Results and Predictive Capacities Reliable and Trustworthy?”, Public Debate, University of Plymouth, 23 April June 2021 (Keynote speaker). 
• “Machine Learning and Health Data Analytics”, AI, Machine Learning and Advanced Computing Seminars, UKRI CDT, 10 June 2020.
• “Machine Learning and Natural Language Processing with Electronic Health Records”, AI and Robotics Symposium, Cardiff University, 27 June 2019 (Keynote speaker). 
• “Harnessing the Power of Machine Learning in Health Data Science: Prediction of the Hospitalisation of Dementia Patients from High-Dimensional Electronic Health Records”, Faculty of Biology, Medicine and Health, the University of Manchester, 8 January 2019 
• “Mining electronic health records to identify influential predictors associated with hospitalisation of dementia patients: An artificial intelligence approach.” Lancet Public Health Conference, Belfast, 23 November 2018. 
• “Artificial Intelligence in Healthcare: Issues, Challenges and Opportunity”, International Centre of Swansea University, UK; Sichuan Tourism University, China, 15 June 2018. 
• “Big Data Analytics in Healthcare: Opportunity and Challenges”, International Centre of Swansea University, UK; Shenyang Aerospace University, China; 22 August 2017. 
• “Machine Learning Techniques to Identify and Evaluate Interactive Risk Factors from Complex Epidemiological Data”, International Symposium on Embracing the Internet of Things to Data-Driven Decisions, Manchester 10~11 June 2016 (Keynote speaker). 
• “Local System Modelling Technique: Quantifying Micro-effect of Domain Factors in Complex Interactions of Epidemiological Data”, International Conference on Engineering and Medical Informatics, Liverpool, 23~24 May 2013 (Keynote speaker).

Conferences Organised:

Shangming has been the chair/co-chair/co-organisier to organise the following conferences or special sessions: 

• Special Session: “Advances on eXplainable Artificial Intelligence” for the 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2021).
• Pre-conference Workshop on Machine Learning for the 2016 International Population Data Linkage Conference (IPDLN2016).
• Special Session: “Towards Intelligent Computing for Complex and Big Data Analysis in e-Health,” for 2014 IEEE World Congress on Computational Intelligence (WCCI 2014).
• Special Session: “Healthcare and Enterprise Systems,” for 2013 IEEE International Conference on Systems, Man and Cybernetics (SMC 2013).
• Co-chair of Program Committee for 2013 World Congress on Intelligent Systems (GCIS 2013).
• Publication Chair for the 3rd World Congress on Intelligent Systems, 2012.
• Special Session: “Computational Intelligence and Cyber-infrastructure for Data Mining and Complex System Modelling in Medical Informatics and e-Health”, for 2010 World Congress on Computational Intelligence (WCCI).
• Chair of Program Committee for 2009 World Congress on Intelligent Systems (GCIS 2009)
• Co-chair of Program Committee for 2009 World Congress on Software Engineering (WCSE 2009)
• Special Session: “Approaches to Managing Linguistic Information in Soft Decision Making: Theory and Applications,” for 2008 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2008).
• Special Session-“Swarm Intelligence III”, for 2008 IEEE International Congress on Evolutionary Computation (CEC).