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Companion Robot Development based on Multimodal Emotion Recognition for Mental Health Applications

EPSRC DTP PhD Studentships: Specific Project Advert

Applications are invited for our EPSRC funded Doctoral Training Partnership (DTP) PhD studentship for the project “Companion Robot Development based on Multimodal Emotion Recognition for Mental Health Applications” starting 1st October 2021. Successful applicants will receive an annual stipend (bursary) of £17,609, including inner London weighting, plus payment of their full-time tuition fees for a period of 36 months (3 years).

The majority of studentships are available to applicants who are eligible for home (UK) tuition fees but a limited number are available to overseas and EU nationals who meet the academic entry criteria.

The Project

You will join the internationally recognised researchers in the Department of Electronic and Electrical Engineering, Centre of AI and Intelligent Digital Economy and Society. This exciting research project is focused on the development of a companion robot especially with advanced emotion recognition ability from multiple modalities. Apart from current deep learning models, neuromorphic computing models will be considered as it can simulate human brain architecture and behaviour for reasoning, pattern recognition, and decision making. The companion robot will be specially designed for mental health applications with the capability of recognising human emotions and take suitable interactions with human beings.

Please contact Dr Hongying Meng at Hongying.meng@brunel.ac.uk to arrange an informal discussion about the project.



Skills and Experience

Applicants will be required to demonstrate their ability to develop neural network models for emotion recognition, feature extraction and multiple modality fusion; develop and implement real-time algorithms at multiple platforms with strong programming skills. You should be highly motivated, able to work independently as well as in a team, collaborate with others and have good communication skills. Experience in machine learning/deep learning algorithm development, robot design, sensor interfacing, signal acquisition, signal processing, and programming in MATLAB, C++, Python, Java, etc will be desirable.

Academic Entry Criteria

You will have or be expected to receive a 1st class or 2:1 honours degree in Electrical, Electronic and Computer Systems Engineering or a similar discipline. A Master degree is not required but may be an advantage. If applicable, you should hold an English Language proficiency qualification of or equivalent to an overall score of IELTS 6.5 (minimum 6.0 in all sections).

How to apply

Please submit the documents below) to cedps-pgr-office@brunel.ac.uk by Noon on Friday 4 June 2021. Interviews will take place in June/July 2021.

  • Your up-to-date CV;
  • Your personal statement (300 to 500 words) summarising your background, skills and experience;
  • Your Undergraduate/Postgraduate Masters degree certificate(s) and transcript(s);
  • Your English Language qualification, if appropriate;
  • Contact details for TWO referees, one of which can be a member of Brunel University academic staff.

Remember to state the title of the project at the top of your personal statement.

Meet the Supervisor for this Studentship

Hongying Meng - Dr Hongying Meng is a Reader with Department of Electronic and Electrical Engineering, College of Engineering, Design and Physical Sciences, Brunel University London. Before that, he held research positions in several UK universities including University College London (UCL), University of York, University of Lincoln, University of Dundee and University of Southampton. He received his Ph.D. degree in Communication and Electronic Systems from Xi’an Jiaotong University and was a lecturer in Electronic Engineering Department of Tsinghua University, Beijing in China. He is a Member of Engineering Professors’ Council, and a Fellow of The Higher Education Academy (HEA) in UK. He is a Senior Member of IEEE and an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Cognitive and Developmental Systems (IEEE TCDS), and a general chair for 16th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2020).