The COVID-19 pandemic accelerated the growth of digital economy. Aside from the business-critical remote communication software, it is surprising to see the fast growth of the entertainment industry backboned by visual content generation. For example, there was a 34% surge of UK installation of TikTok for the week when the lockdown was enforced [1]. Such a surge implies a two-fold contribution of visual content generation in fighting COVID-19:
1) It protects people’s mental health during the self-isolation, lockdown, and even curfew. Almost all the 66 million people in the UK are affected by the daily upgraded restriction rules [2]. Thus, it is critical to protect their mental health and prevent them from being “the ignored majority”.
2) It creates more “contactless” jobs. “I cannot protect every job.” said Rishi Sunak [3]. This reveals an urgent demand for new job opportunities. Fortunately, this demand can be met by becoming visual content creators who earn their livings by publishing contents on platforms like Patreon, Youtube and Tiktok.
However, high-quality visual content can be difficult to create. This motivated Artificial Intelligence (AI) to join the game. Nevertheless, ethical concerns arise as deep neural networks, the backbone of modern AI, suffer from the interpretability problem and can be “unconsciously biased”. For example, a recent super-resolution method developed by Duke University [4] has a strong racial bias: it converted a low-resolution Obama face to a high-resolution white face [5]. In line with the growing social awareness of BAME+, it is therefore critical to tailor deep generative models for fair and unbiased visual content generation.
Instead of ascribing the biases solely to unbalanced training datasets, we seek an outstanding, talented and ambitious PhD student for carrying out high quality research to fulfil the demands of unbiased AI. Specifically, this project aims to answer three research questions:
1) How to uncover the biases of pre-trained deep generative models?
2) What biases are implicitly introduced during the training process?
3) How to create fair and unbiased deep generative models?
From the student’s perspective, the distinctive benefit of this studentship is the development of both technical skills and the awareness of how technologies (especially AI) impact the society and economy. On one hand, it widens the job opportunities for the student upon graduation: in addition to technical jobs in academia and companies like Google and Facebook, the student will also be a good fit for government and third sector jobs on the regulation of AI; on the other hand, with the increasing public attention on the fairness of AI, the student will have chance to make a great impact by publicising his/her research via media, influencing policymakers and applying his/her research findings to the practical problems faced by the industry (e.g. Adobe).
Successful candidates will join the Visual Computing Group in the School of Computer Science and Informatics, experience a vibrant research culture and be aligned with our strategy in doing world-leading research. You will have access to excellent computing facilities, including clusters and cloud environments, a dedicated GPU processing farm and the University's multi-million pound Advanced Research Computing facility (ARCCA).
Successful candidates will also benefit from the training sessions offered by the Doctoral Academy, the seminars organized by different research groups, the mentoring from members in the supervisory team, and the peer-support from research lab colleagues.
For more information on this project, please contact the supervisor, Dr Yipeng Qin, [Email Address Removed]
Entry requirements
Students must meet the criteria, outlined in the terms and conditions, see the UKRI Website (https://www.ukri.org/our-work/developing-people-and-skills/find-studentships-and-doctoral-training/get-a-studentship-to-fund-your-doctorate/). There have been recent changes to UKRI eligibility, details available on the above website.
Studentships are available for Home and International students, with up to 30% of studentships being available for international applicants. This will be managed on a first-come first-serve basis.
Academic criteria
A 2:1 Honours undergraduate degree or a master's degree, in computing or a related subject. Applicants with appropriate professional experience are also considered. Degree-level mathematics (or equivalent) is required for research in some project areas.
Applicants for whom English is not their first language must demonstrate proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skill component.
Applications and Interviews
Deadline for submission of CV and cover letter to supervisors: 9th July 2021
Deadline for full online application (may be extended if necessary): 9th July 2021
Apply now: https://www.cardiff.ac.uk/study/postgraduate/research/programmes/programme/computer-science-and-informatics In the funding field of your application, indicate “I am applying for EPSRC DTP PhD Scholarship in Computer Science and Informatics”, and specify the project title and supervisors of this project in the text box provided.
Interview - If the application meets the entrance requirements, you will be invited to an interview.
Expected week of interview: TBC
Expected week of outcome to applicant: two weeks after interview.
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