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PhD Studentship - Synthetic Facial Generation and Trustworthy AI Models for Continuous Biometric-based Authentication

University of Plymouth

Qualification Type: PhD
Location: Plymouth
Funding for: UK Students, International Students
Funding amount: £19,088 - please see advert
Hours: Full Time
Placed On: 19th January 2024
Closes: 15th March 2024

DoS Professor Nathan Clarke (nathan.clarke@plymouth.ac.uk, tel.: +44 1752 586218)

2nd Supervisor Dr Hai-Van Dang (hai-van.dang@plymouth.ac.uk)

3rd Supervisor Professor Mona Nasser (mona.nasser@plymouth.ac.uk)

Applications are invited for a three-year PhD studentship. The studentship will start on 1st October 2024.

Funding amount: The studentship is supported for 3 years and includes full Home tuition fees plus a stipend of £19,088 per annum 2024/25 rate (TBC).

Project Description

Social robots have an increasingly important role across a variety of dental-based interventions. Trust from patients is however critical in ensuring successful adoption. A key first step is in ensuring correct identification of the patient and to do so on a continuous basis – to minimise potential mistreatments. Whilst much research has been undertaken within facial recognition, this has focussed upon environments where facial orientation, distance and illumination can all be carefully controlled. In this context, not only could facial images be obscured but due to dental treatment, the face may be temporarily deformed or enlarged.

This project will seek to develop more robust and trustworthy facial recognition through exploring the role of pseudo-synthetic facial reconstruction to aid in the creation of suitably formatted facial images for use within facial recognition classification systems. Capitalising upon advances in Generative Adversarial Networks (GANs), the project will explore the viability and quality of facial recognition using varying proportions of genuine face samples.

Given the focus upon synthetic facial reconstruction, it is also essential the resulting classifier obtains an appropriate balance in the feature vector to minimise any potential targeted attacks. As such, the second focus is on the application of explainable machine learning to ensure trustworthiness.

The project aim will seek to enhance the performance of continuous facial recognition through:

  1. Investigating the role of synthetic facial reconstruction for overcoming weakness in facial image quality and
  2. The development of novel explainable machine learning to ensure resulting classifications are trustworthy.

Eligibility

Applicants should have a first or upper second class honours degree in an appropriate subject and preferably a relevant Masters qualification. Applications from both UK and overseas students are welcome.

The studentship is supported for 3 years and includes full Home tuition fees, Bench fee plus a stipend of £19,088 per annum (2024/25 rate TBC).  The studentship will only fully fund those applicants who are eligible for Home fees with relevant qualifications. Applicants normally required to cover International fees will have to cover the difference between the Home and the International tuition fee rates. The international component of the fee may be waived for outstanding international applicants.

NB: The studentship is supported for three years of the four-year registration period. The fourth year is a self-funded ‘writing-up’ year.

If you wish to discuss this project further informally, please contact Professor Nathan Clarke, (nathan.clarke@plymouth.ac.uk).

To apply for this position please click the Apply’ button.

Please clearly state the name of the DoS and the studentship title that you are applying for on the top of your personal statement.

Please see here for a list of supporting documents to upload with your application.

For more information on the admissions process generally, please contact research.degree.admissions@plymouth.ac.uk

The closing date for applications is 12 noon on 15th March 2024. Shortlisted candidates will be invited for interview shortly thereafter. Applicants who have not received a response within six weeks of the closing date should consider their application has been unsuccessful on this occasion.

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