In this project the PhD research student needs to understand the strengths and weaknesses of the emerging semi-supervised and unsupervised deep learning networks for analysing videos. Also the spatio-temporal cues that arise from understanding the subtle human behaviours in short videos. The student needs to study, analyse and conduct experiments systematically on large databases to model and design new semi-supervised and/or unsupervised deep networks that outperforms the current-state-of-the algorithms.
These are active and important areas of research with many opportunities for innovation and collaboration. This project will provide an opportunity to pursue world-class research environment, provide experience of design and evaluation processes and an opportunity for substantial contribution to international publication in leading journals/conference proceedings.
Keele University is renowned for its exciting approach to higher education and research, beautiful campus, strong community spirit and excellent student life. The University has the UK’s largest campus with 617 acres of landscaped parkland, fields, woodlands and lakes. Keele University runs its own day nursery for infants from 3 months to 5 years and is committed to equality and diversity. Information for prospective postgraduate researchers can be found here: http://www.keele.ac.uk/pgresearch/
Research Context: This PhD project will be a part of human activity recognition collaborative research inspired by analysing subtle and specific behaviour analysis of humans. The research will be supervised by Dr Bappaditya Mandal in the Centre for Computer Science Research at Keele University and collaboration with Caudwell International Children Centre at Keele University, and potentially, with other national and international project partners. Caudwell International Children’s Centre, Keele Science & Innovation Park, Innovation Way, Newcastle-under-Lyme, Newcastle ST5 5NT. https://www.caudwellchildren.com/new_autism_centre/
Applications are welcomed from science, technology, engineering or mathematics graduates with (or anticipating) at least a 2.1 honours degree or equivalent. Applicants will require good general computing skills but will not need specific computing expertise in, for example, Computer Vision, Machine Learning and Video Analytics.
Applicants should have an enthusiasm for design and experimentation as well as a willingness to acquire new skills. Ideally, applicants will be self-motivated and have the ability to work both independently and as part of a team.
This opportunity is open to UK/EU and overseas students. The collaborative and presentation aspects of the research require good English language and communication skills. Overseas applicants would therefore require an English IELTS (or equivalent) of 6.0 overall with no less than 5.5 in any subtest.
Applicants should be self-motivated and enjoy working both independently and as part of a team.
Subject areas: Computer Vision, Deep Learning, Machine Learning, Image and Signal Analysis, Video Analytics, Pattern Recognition, Semi-supervised and unsupervised learning, Human Behavioural and activity analysis, Generative and Adversarial Models, Biomedical Engineering
Informal enquiries about the project are very welcome by email to the Project Lead, Dr Bappaditya Mandal ([email protected]
). Full applications should be submitted to: https://www.keele.ac.uk/study/postgraduateresearch/researchareas/computerscience/
Please ensure you quote FNS GS 2019-08 on your application.
Keele University values diversity, and is committed to ensuring equality of opportunity. In support
of these commitments, Keele University particularly welcomes applications from women and from
individuals of black and ethnic minority backgrounds for this post. The School of Computing and
Mathematics and Keele University has been awarded Athena Swan Bronze, and Keele University
is a member of the Disability Confident scheme. More information is available on these web
pages: https://www.keele.ac.uk/equalitydiversity/ https://www.keele.ac.uk/athenaswan/ https://www.keele.ac.uk/raceequalitycharter/disabilityconfident/