This research develops engineered ultrasonic reporters that allow ultrasound imaging to detect molecular activity rather than only anatomical structure. By targeting biological signals associated with cancer progression and cellular communication, the work aims to distinguish aggressive disease earlier and improve precision medicine through real-time, noninvasive monitoring of underlying cellular behavior.

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 research uses advanced brain imaging, long-term clinical monitoring, and sensor data to understand why deep brain stimulation helps Essential Tremor patients—and why it sometimes stops working. By modelling neural pathways and analysing two-year outcomes, the project identifies optimal DBS targets and the main causes of treatment failure, improving long-term patient care.