Visual analytics interfaces for human-machine collaboration in data analysis
- Funded PhD project: Worldwide (International, UK and EU)
- Value: Funding covers the cost of fees and provides a maintenance matching the Research Council UK rate (£14,553 for 2017/18).
- Number of awards: Funding for this award is not guaranteed. This research project is in competition for funding with other projects and will be awarded on a competitive basis.
- Deadline: 30/03/2018
- Supervisors: Contact Professor Roy Ruddle to discuss this project further informally.
Visual analytics combines human-in-the-loop decision making with powerful computation to let people analyse data that is impossible to make sense of by visualization or automated computation alone. Similar to collaborative user interfaces (https://doi.org/10.1016/j.cag.2009.01.001), we may classify visual analytic interfaces (VAIs) in terms of time (synchronous vs. asynchronous) and dominance (equal partners vs. master-slave). In synchronous VAIs the computation provides real-time feedback to users, whereas asynchronous VAIs involve more complex or greater scale computation but the feedback suffers from time-delays of seconds or even hours. With equal partners there is tight-knit interplay between user and computation, whereas master-slave VAIs trend toward computational steering (user-driven) or multiple compute-visualize-compute iterations (computation-driven).
This project is divided into three parts: (1) use the time-dominance classification to characterise the visual analytic interfaces that are used in today’s applications and the tasks that users need to perform, (2) design and implement exemplars of those interfaces, and (3) compare the interfaces using controlled user experiments to identify the best approaches for VAIs and the circumstances under which they are effective. The experiments will use analysis scenarios drawn from a real application (e.g., driving simulation, astronomy, health or genomics).
Applications are invited from candidates with a minimum of a UK upper second class honours degree (2:1), and/ or a Master's degree in a relevant subject. We also recognise relevant industrial and academic experience.
How to apply
Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section of your application, the name of the PhD you wish to apply for is 'Visual analytics interfaces for human-machine collaboration in data analysis' as well as Professor Roy Ruddle as your proposed supervisor. In the funding section, please state 'School of Computing Funded Studentships' as your sponsor.
If English is not your first language, you must provide evidence that you meet the University’s minimum English Language requirements.
We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.
If you require any further information please contact the Graduate School Office
e: email@example.com, t: +44 (0)113 343 8000.