Andrew Willis

Andrew Willis

Andrew is Bryok’s senior quantitative analyst, responsible for investigating innovate new ways to monitor financial market data and seek anomalous events.  He is leading Bryok's research project into anomaly detection in complex market data.

Andrew is an experienced quantitative analyst/developer in data mining, statistical pattern recognition and signal processing.  He has an outstanding and long track record in applying advanced techniques to successfully solve complex problems for a wide range of clients, worldwide, in a variety of sectors.  His pioneering work has seen him invent/design many of his own functions (and interface with those drawn from MatLab Toolboxes) including such techniques as Principal Components Analysis (PCA), Independent Components Analysis (ICA), Support Vector Machine (SVM), Wavelets, Hidden Markov Models (HMM), Markov Chain Monte Carlo (MCMC), Fisher Discriminant Analysis, Neural Networks and Signal Processing, to name but a few.

Before joining Bryok, Andrew was a senior data analyst at Exxon Mobil in Alberta, Canada, where he developed statistically-based condition monitoring systems for oil extraction processes.  These produced audited cost savings of over $10 million a year, in one unit alone.  During this time he was appointed as adjunct professor at University of Alberta in Edmonton, Canada.  In Utilities, Andrew developed a fault detection and location algorithm (patented by GE), as well as building protection algorithms for the North American power grid.

Prior to joining industry in 1995, Andrew graduated from Cambridge University and was a tenured academic and researcher at a number of Universities including University College and Imperial College London.  He has over 50 refereed papers and conference proceedings to his credit.  While in academia he led a research group in statistical signal processing, and pattern recognition - which pioneered the development of information engineering in industry.


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