Knowledge Representation and Reasoning

PGR-P-302

Key facts

Type of research degree: PhD
Application deadline: Ongoing deadline
Project start date: Tuesday 1 October 2024
Country eligibility: International (open to all nationalities, including the UK)
Funding: Competition funded
Source of funding: University of Leeds
Supervisors: Dr John Stell
Schools: School of Computing

<h2 class="heading hide-accessible">Summary</h2>

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

<h2 class="heading hide-accessible">Full description</h2>

• 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. • Fusing spatially located sensor data 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. • Learning language semantics from video data 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. • Mathematical Morphology for Graphs 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. 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  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. 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. • Level of Detail in Knowledge Representation 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. 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. 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.

<h2 class="heading">How to apply</h2>

Formal applications for research degree study should be made online through the <a href="https://www.leeds.ac.uk/research-applying/doc/applying-research-degrees">University's website</a>. Please state clearly in the Planned Course of Study section that you are applying for PHD Computing FT, 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 and in the finance section, please state clearly the funding that you are applying for, if you are self-funding or externally sponsored. If English is not your first language, you must provide evidence that you meet the University's minimum English language requirements (below). As an international research-intensive university, we welcome students from all walks of life and from across the world. We foster an inclusive environment where all can flourish and prosper, and we are proud of our strong commitment to student education. Across all Faculties we are dedicated to diversifying our community and we welcome the unique contributions that individuals can bring, and particularly encourage applications from, but not limited to Black, Asian, people who belong to a minority ethnic community, people who identify as LGBT+ and people with disabilities. Applicants will always be selected based on merit and ability. Applications will be considered after the closing date.  Potential applicants are strongly encouraged to contact the supervisors for an informal discussion before making a formal application. We also advise that you apply at the earliest opportunity as the application and selection process may close early, should we receive a sufficient number of applications or that a suitable candidate is appointed. Please note that you must provide the following documents in support of your application by the closing date of 3 April 2024 for Leeds Opportunity Research Scholarship or 8 April 2024 for Leeds Doctoral Scholarship: <ul> <li>Full Transcripts of all degree study or if in final year of study, full transcripts to date</li> <li>Personal Statement outlining your interest in the project</li> <li>CV</li> </ul>

<h2 class="heading heading--sm">Entry requirements</h2>

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.

<h2 class="heading heading--sm">English language requirements</h2>

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.5 overall with at least 6.5 in writing and at 6.0 in reading, 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.

<h2 class="heading">Funding on offer</h2>

Self-Funded or externally sponsored students are welcome to apply. UK – The <a href="https://phd.leeds.ac.uk/funding/209-leeds-doctoral-scholarships-2022">Leeds Doctoral Scholarships</a> and <a href="https://phd.leeds.ac.uk/funding/234-leeds-opportunity-research-scholarship-2022">Leeds Opportunity Research Scholarship</a> are available to UK applicants (open from October 2023). <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds. Non-UK –The <a href="https://phd.leeds.ac.uk/funding/48-china-scholarship-council-university-of-leeds-scholarships-2021">China Scholarship Council - University of Leeds Scholarship</a> is available to nationals of China (now closed for 2024/25 entry). The <a href="https://phd.leeds.ac.uk/funding/73-leeds-marshall-scholarship">Leeds Marshall Scholarship</a> is available to support US citizens. <a href="https://phd.leeds.ac.uk/funding/60-alumni-bursary">Alumni Bursary</a> is available to graduates of the University of Leeds. Important:  Any costs associated with your arrival at the University of Leeds to start your PhD including flights, immigration health surcharge/medical insurance and Visa costs are not covered under these studentships. Please refer to the <a href="https://www.ukcisa.org.uk/">UKCISA</a> website for information regarding Fee Status for Non-UK Nationals.

<h2 class="heading">Contact details</h2>

For further information about your application, please contact Doctoral College Admissions by email to <a href="mailto:EMAIL@leeds.ac.uk">p</a><a href="mailto:phd@engineering.leeds.ac.uk">hd@engineering.leeds.ac.uk</a> For further information regarding the project, please contact Dr John Stell by email to <a href="mailto:J.G.Stell@leeds.ac.uk">J.G.Stell@leeds.ac.uk</a>

<h3 class="heading heading--sm">Linked research areas</h3>