Sheng-Ya Wang

Sheng-Ya Wang graduated from the University of Auckland with a Bachelor of Engineering (Honours) and a Bachelor of Science degree majoring in Biomedical Engineering, Chemistry, and Statistics. Her Honours project focused on optimising a MATLAB workflow to fit a finite element model that approximates 3D strains throughout the left ventricle from DENSE image-derived displacements. She has research experience implementing and refining convolutional neural networks for supervised keypoint detection on spinopelvic radiographs, as well as developing image processing algorithms for laser speckle imaging to enhance image registration accuracy.

Sheng-Ya joined CEMRG in 2025 as a PhD student, developing and calibrating mathematical models of the cardiopulmonary system. Her work aims to investigate the dynamic interactions between cardiovascular and respiratory control mechanisms to predict physiological responses across various states, such as exercise.