My main research interest is the detection of abnormalities in biosignals. Processing methods include time-frequency analysis, wavelet analysis, mathematical modelling and various forms of artificial intelligence, including machine learning techniques and neural networks. Applications include electroencephalogram (EEG) signals for binaural hearing research, acceleration photoplethysmogram (APG) and electrocardiogram (ECG) signals for heat stress detection and detection and prediction of breast cancer, cardiovascular disease and kidney disease using various forms of artificial intelligence.

Current PhD opportunities include quantification of binaural hearing using EEG signals and detection or prediction of cardiovascular disease, breast cancer and kidney disease using machine learning techniques.  For further information about research activities and facilities, refer to the information of the Biomedical Engineering and Health Informatics Research Group of CDU at https://www.cdu.edu.au/engineering-it-environment/engineering/research/biomedical-engineering.