A fully funded 3.5-year PhD position is available to work with Dr Rita Borgo (Department of Informatics, King’s College London) connected to the research aims and priorities of the UKRI funded ‘UK TAS-Hub’ project (www.tas.ac.uk).
Trusted AI for Safe Stop and Search
The main objective of this project is to develop AI techniques to analyse behaviours in Stop and Search (S&S) operations. The AI system will be used to inform future operations, avoid unnecessary escalations that jeopardise the safety of the officers (and the searched people) and increase trust in S&S operations.
To this end, we will investigate techniques based behavioural models from state of the art in Social Science, Psychology and Criminology. These models will be integrated with manual coded data from a rich dataset of video recordings from past Stop and Search operations by the London Metropolitan Police. Resulting models will be applied to identify and extract visual signatures from videos and audio sequences . A main objective will also be the development of a visual analytic tool for automatic analysis and labelling of recorded sequences to identify patterns and causal relations, explaining the role of different events in a potential (de-)escalation of the Stop and Search operation.
The theories and tools in this project will be initially developed and evaluated for the specific abstractions (e.g., events and durations) in the particular domain of Stop and Search operations. However, we will ensure that they are transferable to other systems, e.g., using the case studies from the TAS Hub and Verifiability Node, ensuring the transformative value of the research for the broader domain of Safe and Trusted AI.
 State of the Art Report on Video-Based Graphics and Video Visualization (R. Borgo, M. Chen, B. Daubney, E. Grundy, G. Heidemann, B. Höferlin, M. Höferlin, H. Leitte, D. Weiskopf, X. Xie)
 M. Chen, R. Botchen, R. Hashim, D. Weiskopf, T. Ertl and I. Thornton, "Visual Signatures in Video Visualization," in IEEE Transactions on Visualization and Computer Graphics, vol. 12, no. 5, pp. 1093-1100, Sept.-Oct. 2006, doi: 10.1109/TVCG.2006.194.
This project align with all three grand challenges of the UK TAS-Hub: (1) To ensure TAS improve rather than harm our physical and mental wellbeing (as security and privacy will need to go hand in hand with safety), (2) To ensure TAS safeguard rather than undermine our personal freedoms (as these freedoms are explicitly part of the security and privacy questions), (3) To ensure TAS benefit rather than damage our society and the economy (as security and privacy are cornerstones of our society and economy)
The applicant will have access to additional training and networking events through the TAS Doctoral Training Network. The UKRI Trustworthy Autonomous Systems (TAS) Hub is a collaboration of researchers and industry partners working on world-leading best practices for trustworthy and trusted ‘socially beneficial’ autonomous systems. The Network offers PhD students opportunities to share their research with different audiences, to participate in research projects and to engage with academic staff and industry partners. Activities include seminars, workshops, summer school sessions and student conferences.
Applicants will normally be expected to have a Distinction in an MSc or MSci in Computer Science or a related discipline, or an outstanding First-Class BSc qualification, but all applications will be considered on merit as appropriate to the individual case. Applications from individuals with non-standard backgrounds are encouraged, as are applications from women, disabled and Black, Asian and Minority Ethnic (BAME) candidates, who are currently under-represented in the sector.
Funding is available for 3.5 years and includes a tax-free stipend at the standard UKRI rate, full time (UK) PhD tuition fees, and an allowance for research consumables, additional training, conference attendance, etc.
Eligibility is based on residency rather than nationality. Only UK residents are eligible for a full studentship.
Early applications are encouraged. Applicants are strongly encouraged to contact the supervisor (Dr Rita Borgo ([Email Address Removed]) to discuss their interest.
Formal applications should include a short (1-2 page) research proposal based on the above project brief. Anyone making a formal application is advised also to inform the lead academic that they are doing so.
To be considered for the position candidates must apply via King’s Apply online application system. Details are available at https://www.kcl.ac.uk/informatics/postgraduate/research-degrees
Please indicate the supervisor and quote 'PhD studentship in Trustworthy Autonomous Systems' in your application and all correspondence.
The selection process will involve a pre-selection on documents and, if selected, will be followed by an invitation to an interview. If successful at the interview, an offer will be provided in due time.