- Type of research degree
- Application deadline
- Ongoing deadline
- Country eligibility
- International (open to all nationalities, including the UK)
- Dr John Stell
- School of Computing
There are many opportunities for PhD research within this theme. The list below is a selection of some of these opportunities. This list is by no means definitive and you should feel free to contact staff to discuss your own interests: • Representing and Reasoning with Spatial and Temporal Information. • Modelling and Recognition of Events and Activities. • Applications of KRR to: computer vision, geographic information, and biological information. • Ontology Development. • Dealing with Vague and Ambiguous Information. • Analysing sensor data to produce high level interpretations. • Modelling individual users, groups, and knowledge sharing communities to build. • User-Adaptive Systems through the use of ontological reasoning, dialogic models, and graph mining. • Learning qualitative behaviour models Leeds has established itself as a centre for learning behavioural descriptions using qualitative spatio-temporal calculi from video data with a number of PhD theses already completed in this area. There are many more possible PhD topics, for example focussing on more extended behaviours, more complex events, temporally/spatially dependent behaviours, periodic/cyclic behaviours.
<p>There are many opportunities for PhD research within this theme. The list below is a selection of some of these opportunities. This list is by no means definitive and you should feel free to contact staff to discuss your own interests:</p> <ul> <li>Representing and Reasoning with Spatial and Temporal Information.</li> <li>Modelling and Recognition of Events and Activities.</li> <li>Applications of KRR to: computer vision, geographic information, and biological information.</li> <li>Ontology Development.</li> <li>Dealing with Vague and Ambiguous Information.</li> <li>Analysing sensor data to produce high level interpretations.</li> <li>Modelling individual users, groups, and knowledge sharing communities to build.</li> <li>User-Adaptive Systems through the use of ontological reasoning, dialogic models, and graph mining.</li> </ul> <p>• Learning qualitative behaviour models<br /> Leeds has established itself as a centre for learning behavioural descriptions using qualitative spatio-temporal calculi from video data with a number of PhD theses already completed in this area. There are many more possible PhD topics, for example focussing on more extended behaviours, more complex events, temporally/spatially dependent behaviours, periodic/cyclic behaviours.</p> <p>• Fusing spatially located sensor data<br /> The Mapping the Underworld (MTU) project aims to build maps of utilities buried underground based on the expectations of inaccurate maps from the utilities and using surveys of street furniture (e.g. manholes) and data from a multi-sensor "cart" being built by the MTU project. This PhD would build on the existing work in the project.</p> <p>• Learning language semantics from video data<br /> The idea of this project is to try to learn semantics of language describing actions/behaviours from language-annotated video. For example, imagine a cookery programme where a description is being given of actions including cutting and slicing. The spatio-temporal behaviour of the agent involved is similar in both these cases, and the learned semantics for "cut" and "slice" should reflect this.</p> <p>• Mathematical Morphology for Graphs<br /> Mathematical morphology comprises a variety of techniques in image processing which have an algebraic foundation in lattice theory. The basic operations for binary (black and white) images work on a set of pixels. By using different structuring elements we can filter the set of pixels to achieve a modified version of the original image. Although the techniques have been developed in an image processing context, some of the operations are applicable more generally.</p> <p>The operations of dilation, erosion, opening and closing can be described as approximating a subset of set with respect to a relation on the set, and there are <br /> connections between this and rough set theory. There have been a number of proposals for extending some morphological operations from sets to graphs or hypergraphs. One motivation for this generalization is to see whether useful ways of approximating subgraphs of a graph can be described in this way. This could be valuable for viewing graphs at different levels of detail, or possibly for processing a graph (e.g. a social network) to reveal key features in a similar way to filtering an image.</p> <p>This PhD project would develop the theory of mathematical morphology for graphs using a notion of a relation on a graph. It would also implement a variety of morphological operations and apply these in a suitable application domain such as social network data.</p> <p>• Level of Detail in Knowledge Representation<br /> Different tasks require knowledge at different levels of detail. An apparently simple everyday task such as opening a door needs a different level of detail than is needed to repair the same door. In geographical information maps at different scales show information at different levels of detail. In scientific research relationships between descriptions of a process at different levels of detail are often significant. These examples are well-known, but there are several challenging questions when we consider moving between different levels of detail in knowledge represented in a formally specified ontology.</p> <p>This PhD project would investigate mechanisms for representing and reasoning about knowledge at different levels of detail in Description Logics. It would develop ways to translate knowledge between different levels of detail. The techniques would be evaluated in ontologies for geographical information, or another suitable application domain. </p>
<p>Formal applications for research degree study should be made online through the <a href="https://www.leeds.ac.uk/info/130206/applying/91/applying_for_research_degrees">University's website</a>. Please state clearly in the research information section that the research degree you wish to be considered for is ‘Knowledge representation and Reasoning’ as well as <a href="https://engineering.leeds.ac.uk/staff/258/john_stell">Dr John Stell</a> as your proposed supervisor.</p> <p>If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below).</p> <p><em>We welcome 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.</em></p>
Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.
The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.
<p>Self funded students only.</p>
<p>For further information regarding your application, please contact Doctoral College Admissions by email: <a href="mailto:EMAIL@leeds.ac.uk">p</a><a href="mailto:email@example.com">firstname.lastname@example.org,</a> or by telephone: +44 (0)113 343 5057</p> <p>For further information regarding the project, please contact Dr John Stell by email: <a href="mailto:J.G.Stell@leeds.ac.uk">J.G.Stell@leeds.ac.uk</a></p>
<h3 class="heading heading--sm">Linked funding opportunities</h3>