Quantitative evaluation of creativity using computational semantics

Start Dates: Either: 1st October 2018, 1st January 2019, 1st April 2019 and 1st July 2019

Background: Creativity is regarded as one of the most desirable qualities; it involves divergent and convergent thinking. Divergent thinking is particularly important in early stages of product design. It refers to associative and intuitive thought, and thinking that requires flexibility. It is the ability to develop many possible solutions to a problem, some of them unique and novel, which may, though, differ in their quality. Divergent thinking is measured using various models. For example, the Guilford model uses fluency, flexibility, originality and elaboration to measure how creative a person is. On the other hand, the taxonomy of creative design assesses how creative a work is. It classifies creative work as an imitation of another work, a variation on a single work, a combination of two or more works, a transformation of a work into a completely new form, or a creation that is previously unrecognizable.

Project aims and methods: The aim of this project is to develop computational methods based on semantics to measure how creative a person is in the context of the Guilford model and how creative a work is in the context of the taxonomy of creative design. The main innovation is in using computer vision and computational semantics to measure the semantic distance between concepts used in the creative output.

The prospective student is expected to produce high quality journal articles for scientific publication during the course of his/her PhD and would be expected to participate and present his/her research in international conferences.

Research training environment: The student will benefit from an excellent research training environment provided by the High-Value Manufacturing group led by Professor Rossi Setchi.

Person specification: The prospective PhD student is expected to fulfil the following criteria in order to be considered for this position:

• A four year bachelor degree or a master degree in Engineering or Computer Science. Applicants should have obtained, or be about to obtain, a First or Upper Second Class UK Honours degree, or the equivalent qualifications gained outside the UK. Applicants with a Lower Second Class degree will be considered if they also have a Master’s degree.
• Excellent programming skills.
• Strong interest in AI and applying AI to practical engineering problems of industrial relevance.
• Excellent academic track record and communication skills. Relevant evidence includes a conference presentation or journal publication.

Please email Professor Rossi Setchi ([Email Address Removed]) with any queries that you might have regarding the position. Applications are accepted all year round until a suitable candidate is found.