My areas of research are in the development of algorithms and techniques of signal processing, and the application of these techniques in audio, communications and biomedical devices. Signal processing is vital to the economy, because it underpins almost all other scientific and technological endeavour. Most scientific experiments, for example, involve collection of data by some sort of electronic device. Interpretation of this data will involve some sort of signal processing, and superior techniques will result in superior data interpretation. The specific techniques I use include: - Blind Source Separation (BSS) methods such as Independent Component Analysis (ICA), and other adaptive filtering techniques. - Bayesian Filtering methods, including particle filters and unscented filters. - Machine Learning, especially Support Vector Machines (SVM). Areas of application include: - Passive detection of foetal heartbeat. - Seizure detection in neonatal electroencephalogram (EEG). - Cochlear signal detection. - Forward looking sonar signal processing. - Acoustic source localisation and tracking. - Holographic sound recording and reproduction. - Self-calibration of microphone arrays. - Load-bar signal analysis. - Real time prediction of wireless channels.