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School of Electronic Engineering and Computer Science

Multimodal AI for healthcare decision support

Supervisor: Dr Muhammad Salman Haleem

Project Description

This project aims to develop fundamental AI tools for modelling real-time multimodal data to derive advanced healthcare decision support system for effective healthcare management. The research will explore how machine learning can enhance usability of multimodal key enabling technologies for effective chronic disease management and decision support, utilizing diverse data sources. For a glimpse of some of my relevant projects, please have a look here.

PhD topics for this position could explore one or any combination of the following areas:

- Generative AI models: Investigating novel Generative AI approaches to address data quality issues due to missing signal and modalities.

- Multimodal data fusion: Investigating novel multimodal data fusion techniques to derive relationships among different modalities while addressing challenges associated with multimodal fusion complexity for enhanced predictive tasks.

- Multimodal explainability: Investigating the design and development of explainable AI tools capable to support clinical decision making while interpreting multimodal data heterogeneity.

Apart from aforementioned topics, I am also open to supervise a PhD project that explores extracting features from multiple modality types (e.g. real-time signals, medical images, unstructured texts etc.)

Prerequisites:

- A Master’s degree (Distinction or equivalent) or an expected completion of such qualifications before starting the PhD.

- A keen interest in multimodal AI methodologies

- Familiarity with formal reasoning principles.

- Solid programming skills in python and standard ML packages (e.g. tensorflow, pytorch, sklearn etc.), experience in visualization techniques and a drive to create dependable, high-quality automated tool with interactive user interface.

The PhD studentship is funded by EPSRC Doctoral Landscape Award open to those with Home and International fee status. However, the number of students with international fee status who can be recruited is capped according to the EPSRC terms and conditions, so competition for international places is particularly strong. The PhD student will receive an annual stipend of £21,237 for the academic year 2024/25, with funding available for a duration of up to 3.5 years.

How to apply

Queen Mary is interested in developing the next generation of outstanding researchers and decided to invest in specific research areas.

Applicants should work with their prospective supervisor and submit their application following the instructions at: http://eecs.qmul.ac.uk/phd/how-to-apply/.

The application should include the following:

- CV (max 2 pages)

- Cover letter (max 4,500 characters) stating clearly in the first page whether you are eligible for a scholarship as a UK resident (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)

- Research proposal (max 500 words)

- 2 References

- Certificate of English Language (for students whose first language is not English)

- Other Certificates

Please note that in order to qualify as a home student for the purpose of the scholarships, a student must have no restrictions on how long they can stay in the UK and have been ordinarily resident in the UK for at least 3 years prior to the start of the studentship. For more information please see: (https://epsrc.ukri.org/skills/students/guidance-on-epsrc-studentships/eligibility)

Application Deadline

The deadline for applications is the 29th January 2025.

For general enquiries contact Mrs. Melissa Yeo (administrative enquiries) or Dr. Arkaitz Zubiaga (academic enquiries) with the subject “EECS 2025 PhD scholarships enquiry”.

For specific enquiries contact Dr. Muhammad Salman Haleem.

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