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Designing Systems to Extract Meaningful Insights from ’Quantified Self’ Data

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  • Full or part time
    Dr Simon Jones
  • Application Deadline
    Applications accepted all year round
  • Self-Funded PhD Students Only
    Self-Funded PhD Students Only

Project Description

The practice of ‘self-tracking’ has become increasingly popular in recent years through the widespread use of sensor-enriched smart devices, wearable biometric sensors, and online activity logging services. Aggregation and analytics systems, which make use of tracking data, exhibit potential to revolutionise issues such as healthcare, wellbeing, sustainability and energy habits, for example by enabling self-assessment and monitoring, and facilitating behaviour change.

The goal of this project is to understand and address the challenges of designing personal data aggregation and analytics systems. These solutions will take the form of data processing algorithms, interactive data visualizations, and design guidelines to support users in extracting meaningful insights from their data. This research will combine quantitative and qualitative analyses from field and lab studies to test and evaluate the proposed solutions with users.

The successful candidate will be supported to publish work at leading international conferences in the areas of HCI, information visualisation and ubiquitous computing.

The candidate will work closely with Dr Simon Jones, and engage with external collaborators in academia and industry. It is expected that these partners will provide input to the research and collaborate on research studies, and offer opportunities to deliver commercial Impact from the research.

Dr Simon Jones is a Lecturer in Human-Computer Interaction at the University of Bath. His research interests include large-scale data analysis, information visualisation and the design of automated mechanisms to support users of interactive systems. Dr Jones has published his work at leading international conferences including, CHI and UbiComp. He is very keen to support motivated and talented students in developing their research skills. You can find out more about Dr Jones at: or email him to discuss this project at [email protected]

The candidate will join a strong team of postgraduate students working within the Human Computer Interaction group, and will be part of a vibrant student body within the university, with opportunities to interact scientifically and socially.

A PhD in Computer Science from the University of Bath will provide excellent opportunities to develop skills and understanding to shape the technologies that are transforming our world, as a future leader in academic or industrial research.

Training opportunities:
The student will be offered training courses through the University of Bath PG skills programme, whilst also being encouraged to attend international scientific meetings in the areas of HCI, information visualisation and ubiquitous computing. In addition to training opportunities, both subject specific and with a view to developing transferable skills, the student will benefit from collaboration with other institutions working on the interdisciplinary aspects of Personal Informatics, Human-Computer Interaction, Behaviour Change and Healthcare/Assistive technologies.
The student will also have opportunities to engage with the newly formed Bath Institute for Mathematical Innovation within the University of Bath, who specialise in methods for data analysis and mathematical modelling, which will be a core component of the work on the proposed project.

Funding Notes

We welcome all year round applications from self-funded candidates and candidates who can source their own funding.


Jones, S. (2015). Exploring Correlational Information in Aggregated Quantified Self Data Dashboards. New frontiers of Quantified Self Workshop at Ubicomp/ISWC 2015.

Li, I., Dey, A. K., & Forlizzi, J. (2011). Understanding my data, myself: supporting self-reflection with ubicomp technologies. In Proceedings of the 13th international conference on Ubiquitous computing (pp. 405-414). ACM.

Listen to Dr Simon Jones talk of his project in this short video:

How good is research at University of Bath in Computer Science and Informatics?

FTE Category A staff submitted: 24.00

Research output data provided by the Research Excellence Framework (REF)

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