This project developed AI Care, a voice-based caregiving system for people with early-stage Alzheimer's disease. Unlike conventional voice assistants, it uses caregiver-maintained medical records to provide personalised, safety-aware support. By adapting to users rather than requiring users to adapt to technology, AI Care aims to extend safe, independent living at home.

This research uses artificial intelligence to predict the progression of Alzheimer’s disease and cancer using medical imaging data. By analyzing brain scans, tumor scans, and treatment responses, AI models can forecast disease development and treatment outcomes, enabling earlier intervention, more personalized care, and improved quality of life for aging populations.

This study explores anemia as a potential risk factor for dementia, finding that nearly half of dementia patients also exhibit low hemoglobin levels, often undiagnosed. By highlighting links between blood health and cognitive decline, the research advocates earlier detection and a multidisciplinary approach to reduce dementia’s growing societal and healthcare burden.

This research investigates how motion perception changes with age and how these changes are reflected in brain function. Using behavioural tasks and fMRI, the research aims to develop simple visual tests that could be used in routine eye-care settings to identify early signs of cognitive decline and support healthy ageing.

This research investigates how T cells influence microglial behavior in Alzheimer’s disease. Using a mouse model, the study found that removing T cells did not alter amyloid-beta plaques but unexpectedly led to healthier microglial activity and reduced myelin damage. The findings suggest T cells may worsen neurodegeneration and reveal new therapeutic avenues.