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  Human-Computer Interaction and the ‘Quantified Self’: Designing interactive systems that make use of personal tracking or ‘quantified self’ data


   Department of Computer Science

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  Dr Simon Jones  Applications accepted all year round

About the Project

This project has a focus on designing interactive systems that make use of personal tracking or ‘quantified self’ data.

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. Interactive systems which make use of diverse personal data, exhibit the potential to revolutionise issues such as healthcare, wellbeing, sustainability and energy habits, for example by enabling self-assessment and monitoring, and facilitating behaviour change.

This project will focus on understanding and addressing the challenges of designing interactive systems that use personal data. The ideal candidate will have proven experience and skills in Human Computer Interaction, and an interest in areas such as data mining, data visualization, and user interface design. It is expected that this research will combine quantitative and qualitative analyses from field and lab studies to test and evaluate interactive systems with users.

The successful candidate will be expected 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: http://people.bath.ac.uk/cs3sj/ or email him directly to discuss your this project at [Email Address Removed]

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-funding candidates and candidates who can source their own funding.

References

Jones, S. and Kelly, R. (2016). Finding “Interesting” Correlations in Multi-Faceted Personal Informatics Systems. In: SIGCHI Extended Abstracts on Human Factors in Computing Systems 2016, 2016-05-07, San Jose.
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.

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