Department of Applied Mathematics and Theoretical Physics

I research and develop image analysis techniques and apply them to problems in medical imaging -- principally variational and machine learning based methods. In particular, I look to detect imaging or clinical biomarkers indicating disease progression. My background is mathematics and image analysis. Developing new and robust image segmentation methods was my primary research area for my Ph.D. and developing new deep neural networks for medical image segmentation was the focus of my previous postdoc.

I am interested in using mathematical and mechanical tools to describe the biological systems. Better understanding of diseases can be achieved by further analysing the structural and functional imaging data. We hope our work will improve the diagnostic and prognostic values of current imaging modalities, and ultimately aid the risk stratification and clinical management.