Areas of current interest include:
- computer vision
- knowledge representation and ontology
- machine learning
- nature-inspired computing
- shape representation
The department brings together Computer Scientists and Mathematicians working on a variety of modern-day, interdisciplinary topics including problems of knowledge representation, machine learning, optimisation, image and signal processing. We have our own Beowulf parallel machine and access to the University's EPSRC-funded IBM supercomputer SP3 system. For detailed information see our research webpages and staff profiles.
In the area of machine learning, pattern analysis and statistical computation, which incorporates close collaboration with the mathematical sciences, we research a range of techniques for learning from data, including statistical and nature-inspired methods. Current and recent projects in this area have focused around application areas ranging from bio-medical imaging, face and speech recognition to air-traffic control and safety-critical software design. A strong research theme in this area is shape-based computer vision and image processing, particularly for image retrieval and object classification.
Research on optimisation methods focuses on techniques for evolutionary optimisation, particularly multi-objective optimisation. This work is currently being exploited in areas such as hydroinformatics, credit-card fraud detections, mobile phone network turning and bioinformatics problems. Closely related to these is research into biologically inspired algorithms, such as neural networks, swarm intelligence and artificial life, together with applications to bioinformatics.
Artificial intelligence research interests focus on spatial and temporal knowledge representation, with applications to geographical information science, and on the philosophical foundations of artificial intelligence and computer science.
In the area of hydroinformatics we are mainly concerned with the design and multi-objective optimisation of water distribution and related networks using iterative learning algorithms and neural networks; genetic algorithms; water systems. This is supported by EPSRC, EU and British Council contracts. The work involves collaboration with numerous UK and EU universities and industrial companies.
Entry requirements 2018
Requirements for international students
If you are an international student, please visit our international equivalency pages to enable you to see if your existing academic qualifications meet our entry requirements.
English language requirements
Overall score 6.0. No less than 6.0 in any section.
Overall score 87 with minimum scores of 21 for writing, 21 for listening, 22 for reading and 23 for speaking.
Pearson Test of English (Academic)
55 overall with no less than 55 in all communicative skills.
Other accepted tests
Information about other acceptable tests of linguistic ability can be found on our English language requirements page.
Applicants with lower English language test scores may be able to take pre-sessional English at INTO University of Exeter prior to commencing their programme. See our English language requirements page for more information.
Finance: fees and funding
- UK/EU: £4,400 full-time; £2,200 part-time
- International: £23,000 full-time
Current available funding
Postgraduate research admissions
Phone: +44 (0) 1392 722730
Web: Enquire online