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Prediction of Service Demand and Quality of Experience using Deep Learning for Healthcare

About This PhD Project

Project Description


With the explosive growth of services on the Internet, the number of choices is overwhelming. Traditionally services are passively searched by users. More plausibly, services should be actively pushed in meeting user’s potential needs. It has been reported that 93% of the doctors believe that healthcare apps can bring improvement in patient’s health and 80% of the physicians are using the mobile technology to deliver the patient care. This project will focus on mobile application for healthcare. Recently, it has been a hot research area to predict user’s potential demands and QoE (Quality of Experience) values of candidate services. This problem becomes very challenging in the circumstance of mobile Internet, particularly for mobile healthcare applications. Currently solutions for mobile user demand prediction have limitations on the fully use of information from embedded sensors and are unable to address the mobility, security and resource issues effectively.


This PhD project aims to investigate a personalized privacy-preserving and flexible prediction of mobile user’s service demand and the ranking of the candidate services with QoE values. To achieve this goal, data will be collected from heterogeneous sources, and data model for services, users, and invocation relationship between these two will be designed. In order to protect user’s privacy, core users will be identified to filter user’s location and a differential privacy technique will be developed to protect service invocation history. Then, by use of Deep Learning, temporal location evolution models will be constructed; and a context-aware dynamic service demands prediction algorithm will be developed. Finally, a comprehensive QoE ranking algorithm will be developed with the ability to learn user’s preference in different candidate services.


The successful applicant will be…
Include any additional requirements specific to the project. Who do you want to apply? What is the ideal candidate (subject area and degree?)
The successful applicant will hold the minimum of a first degree (2:1 or above). Previous experience data analytics is desirable.

Additional application requirements. Only include the following if you wish the applicant to provide a worked up research proposal for the project or you have other application requirements additional to the standard application materials.
Candidates are requested to submit a more detailed research proposal (of a maximum of 2000 words) on the project area as part of their application.

Research Strategy and Research Profile

Glasgow Caledonian University’s research is framed around the United Nations Sustainable Development Goals, We address the Goals via three societal challenge areas of Inclusive Societies, Healthy Lives and Sustainable Environments. For more. This project is part of the research activity of the Research Group – Artificial Intelligence Research Laboratory.

How to Apply

Applicants will normally hold a UK honours degree 2:1 (or equivalent); or a Masters degree in a subject relevant to the research project. Equivalent professional qualifications and any appropriate research experience may be considered. A minimum English language level of IELTS score of 6.5 (or equivalent) with no element below 6.0 is required. Some research disciplines may require higher levels.

Candidates are encouraged to contact the research supervisors for the project before applying. Applicants should complete the online GCU Research Application Form, stating the Project Title and Reference Number (listed above).

Please also attach to the online application, copies of academic qualifications (including IELTS if required), 2 references and any other relevant documentation.

Please send any enquiries regarding your application to: Applicants shortlisted for the PhD project will be contacted for an interview.

For more information on How to apply and the online application form please go to

Dr Yan Zhang

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