Supervisor View Full Details 2nd

• Other

Data analytics; computer hardware

• Surgery
• Ophthalmology

• Dementia
• Health Informatics

I lead a group of researchers who have been looking at data analytics for a range of applications. We have previously investigated integration of data sources for dementia. It is probably not as relevant, but we have looked at different learning approaches for understanding data in manufacturing and in developing embedded solutions that have low power that are typically used in medical applications. We are just embarking on a project on compact multi-spectral imaging for surgical guidance and diagnostics. We are also exploring some of the challenges in wireless medical technologies. Our underlying approach is the development of computer hardware which can be used to process data at source.

I am particularly interested in developing embedded hardware solutions for processing data in remote or biomedical applications. The main aim is to try and bring intelligence near the patient and thus develop embedded AI technology. In practice, this will involve working with clinicians to develop practical, operational prototypes where the medical decision-making is enhanced by improving the data that is obtained at the various sensors. The prototype solutions will be developed using the sensors currently employed to capture data from the body and advanced computer hardware such as embedded graphical processing units or field programmable gate arrays (FPGAS) which have extremely low power properties. The key challenges performing the computer required with limited power budget. The output would be improved diagnosis systems probably targeted at surgical or ophthalmology. Any prospective students would benefit from a considerable body of expertise that exists within Queens in developing such solutions.