In the modern world, it is commonplace to want to extract knowledge from large-scale data sets, and data mining and analytics techniques are developed and utilised for this purpose. Advanced visual interfaces could assist researchers or data analysts in their knowledge extraction tasks as well as potentially help with the explanation of any outcomes to other stakeholders, such as company managers. Visual aspects may include the specification of complex queries and the returned results in primarily visual format, and visual explanations of prediction (eg examples of similar cases). Whilst some choices of visual representations may be generically useful, they may require additional fine tuning or alternatives to be used according to the particular domain and the tasks to be performed.
The project will focus on the combination of data mining and analytics together with advanced visual interfaces applied with the context of an engineering domain. The Advanced Engineering Centre is part of the UK APC, with interests in the energy/low carbon theme and an overall drive for efficiency and evaluating new approaches to energy usage. The project will have industrial impact via enhancement of capabilities.
A good candidate will have a strong technical background in mathematics, statistics or computing, with demonstrable programming skills. Ideally, the candidate will have a good understanding of either data mining or visualisation, but due to the strong support available for this project, in terms of supervisors, advisors and collaborators, there is flexibility to adjust directions according to the successful candidate’s background and developmental needs.
The project connects distinct areas of computing (eg visual analytics and machine learning) and automotive engineering, and has potential to deliver world leading publications in multiple areas. The deliverables are well suited to publication in a venue such as the high impact journal IEEE Transactions on Industrial Informatics, as evidenced by prior research output, and other deliverables could be targeted at the IEEE Transactions on Pattern Analysis and Machine Intelligence journal and the International Journal of Engine Research, Fuel, or Combustion and Flame.
The research involved is the culmination of many years of research experience of Dr Fish on visual representations, including several EPSRC grants, the research base of the Knowledge Engineering Group which has had heavy focus on future impact via significant funded industrial-facing projects including the longstanding relationship with Network Rail of which Dr Kapetenakis is a vital part, and Dr Begg’s longstanding expertise in the automotive engineering field, including many funded projects, such as CEEREV funded by EU Intereg in which relevant work began.