Paul Teal

Associate Professor School of Engineering and Computer Science

Teaching in 2018

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Research Interests

My areas of research are in the development of algorithms and techniques of signal processing, and the application of these techniques in nuclear magnetic resonance, 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:
  • Convex analysis.
  • Blind Source Separation (BSS) methods such as Independent Component Analysis (ICA).
  • Bayesian Filtering methods.
  • Machine Learning, especially Support Vector Machines (SVM).

Areas of application include:
  • Magnetic resonance (imaging, spectroscopy and relaxometry)
  • Modelling of human physiology (e.g., cerebral haemodynamics)
  • Modelling of cochlear function
  • Passive detection of foetal heartbeat.
  • Seizure detection in neonatal electroencephalogram (EEG).
  • Cochlear signal detection.
  • Forward looking sonar signal processing.
  • Acoustic source localisation and tracking (including bioacoustics).
  • Holographic sound recording and reproduction.
  • Self-calibration of microphone arrays.
  • Load-bar signal analysis.
  • Real time prediction of wireless channels.

I am a member of the Centre for Biodiversity and Restoration Ecology (brochure)

Students

A list of my past students.

Publications

A list of my Publications.

For some recent publications, please see the Publications Database.

Availability:

My calendar is publicly available.