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Department of Computer Science


Arousal and Scanpath Trend Analysis (a-STA)

Primary supervisor

Additional supervisors

  • Markel Vigo

Additional information

Contact admissions office

Other projects with the same supervisor

Funding

  • 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

Eye-tracking studies have widely been used for understanding user behaviour. Even though eye tracking can be used to collect very rich data about user interaction, to make any generalisation one needs to process and typically bring together individual users' data. There are many approaches ranging from very fundamental techniques such as heatmaps to very advanced data mining techniques. In our previous work, we introduced a technique called Scanpath Trend Analysis (STA) that aims to analyse a group of users' eye-tracking data to generate a trending path which is the most popular path followed among a group of users. Even though STA is very successful in identifying this trending path, this path does not give any information about the pupillary response, which is an unobtrusive measure of physiological arousal. We have previously attempted to combine an arousal model with STA. However, the main aim of this project is to research and propose a systematic framework in combining a model of arousal with STA. There are also techniques and systems, such as WevQuery, available that can handle large datasets for identifying and querying web interaction techniques. This PhD project also aims to investigate how such systems and techniques can also be facilitated to combine the STA with the arousal model. To achieve these, the following research questions will have to be addressed:

RQ1. How can we bring together the arousal model with the STA in a framework?
RQ2. Can we facilitate web interaction analysis frameworks such as WevQuery for this purpose?
RQ3. How could the combined approach be compared to STA and the arousal model, and how do they each perform?

To address these questions, the PhD candidate will have to be willing to use a multidisciplinary approach that involves:

- Eyetracking research.
- Data science and algorithms.
- Statistical analysis and visualisations.

For these PhD positions, split-side PhD with Middle East Technical University Northern Cyprus Campus (METU NCC) option is also available. Full PhD Teaching Assistant Scholarship is also available at METU NCC. For further details and for the process of application, please contact Yeliz Yesilada (yyeliz-AT-metu.edu.tr)

Person specification

For information

Essential

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.

Desirable

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

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

General

Applicants will be required to address the following.

  • 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?
  • Comment on your transcript/predicted degree marks, outlining both strong and weak points.
  • Why do you believe you are suitable for doing Postgraduate Research?