Professor of Statistical Signal Processing, Department of Engineering, University of Cambridge
Professor Simon Godsill coordinates an active research group in Signal Inference and its Applications within the Signal Processing and Communications Laboratory at the University of Cambridge. He specialises in Bayesian computational methodology, multiple object tracking, audio and music processing, and financial time series modelling.
Professor Godsill was Technical Chair of the 2006 IEEE NSSPW workshop on sequential and nonlinear filtering methods and has served as Associate Editor for IEEE Tr. Signal Processing and the Bayesian Analysis journal.
The Signal Processing Laboratory is involvement in audio and music processing, its current research is concerned with accurate modelling of digital audio and automated inference about the parameters and structure of those models.
Professor Godsills current research interests include
- Audio signal processing – source separation, music analysis and transcription, noise reduction, audio restoration, multiple channel audio and sparse/overcomplete models
- Tracking – sensor function, multiple object tracking, detection, radar and sonar
- Signal inference methodology – Bayesian and Monte Carlo methods, particulate filter and model uncertainty