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Department of Computer Science

User Modeling for Physical Activity Tracking

Primary supervisor

Additional information

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Other projects with the same supervisor


  • Competition Funded Project (Students Worldwide)

This research project is one of a number of projects at this institution. It is in competition for funding with one or more of these projects. Usually the project which receives the best applicant will be awarded the funding. Applications for this project are welcome from suitably qualified candidates worldwide. Funding may only be available to a limited set of nationalities and you should read the full department and project details for further information.

Project description

Physical activity tracking wearables and apps constitute an environment where user input (set goals, demographics, preferences) and sensed input (steps, calories burnt, heart rate, weather) provide good opportunities to explore user modelling techniques (ie computational representations of users that can be used for personalisation or recommendation purposes). As a result, one could explore factors of interest and test hypotheses (eg "are people more active on sunny days?").

Typically, digital phenotyping studies focus on monitoring health conditions that are chronic, episodic or seasonal, but little attention has been paid to understanding the association of human behaviour and wellness -- although there are a few exceptions, see [1].

This project is about building user models using sensed data and physical activity data in order to explore what are the factors that facilitate/prevent achieving physical activity goals and intervene accordingly. To do so, the PhD project may follow this plan:

1. A review of the literature review and formulation of the research hypotheses
2. Build a physical activity tracking systems using the AWARE framework and its Fitbit plugin.
3. Run longitudinal user studies to collect data.
4. Identify the factors that prevent/facilitate goal achievement and build user models accordingly.
5. Based on personalisation principles (see an extensive review in [2]) and informed by user models, design and evaluate interventions to support users in achieving their physical activity goals.

Consequently, the project would be appropriate for a candidate who is skilled in at least two of the following: software development, experimental design and data science. If one skill was missing, the candidate must show commitment to acquire it during the course of the project. Also, it is expected that the candidate will publish academic papers in SIGCHI venues (CHI, DIS, EICS), UMAP and UbiComp/IMWUT.

Person specification

For information


Applicants will be required to evidence the following skills and qualifications.

  • You must be capable of performing at a very high level.
  • You must have a self-driven interest in uncovering and solving unknown problems and be able to work hard and creatively without constant supervision.


Applicants will be required to evidence the following skills and qualifications.

  • You will have good time management.
  • You will possess determination (which is often more important than qualifications) although you'll need a good amount of both.


Applicants will be required to address the following.

  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Discuss your final year Undergraduate project work - and if appropriate your MSc project work.
  • How well does your previous study prepare you for undertaking Postgraduate Research?
  • Why do you believe you are suitable for doing Postgraduate Research?