Introduction

I have been working in scientific research for the past 10+ years, seeking to combine applied mathematics and probability theory with computer science. In slightly old-fashioned parlance, my primary field of interest might have been described as "artificial intelligence", but "machine learning" may be a better contemporary description.

My research interests have mainly centred on the theory and application of probabilistic models for machine learning and statistical pattern recognition, emphasising the use of Bayesian inference. These strands led to the creation of the relevance vector machine.

I've also spent considerable time working in neural computing, data visualisation, exploratory data analysis, topographic mapping and kernel models. Application fields I have tackled include handwriting recognition, bioinformatics, information retrieval, image processing and interactive entertainment.

Many of my published papers in these areas are available here on this site.

Read on for an expanded summary of what I've been doing for the last few years (in reverse chronological order), including some relevant further links where useful.

Vector Anomaly

Currently, I am running Vector Anomaly, a statistical consultancy which I set up in 2006 along with Mark Hatton. We specialise in the advanced statistical analysis, modelling and processing of data and systems. For more information, feel free to look at our consultancy page and/or contact us directly.

Microsoft Research

From 1998 to 2006, I was a researcher with Microsoft Research (MSR), in Cambridge (UK). I worked primarily on the development and application of probabilistic models in machine learning, as well as many of the other topics mentioned above. In particular, I concentrated on advancing Bayesian methodology for efficient automated prediction and worked on implementations of sparse learning models for regression and classification tasks. This thread of research resulted in the concept of "sparse Bayesian learning" and the popular relevance vector machine.

Latterly at Microsoft, I concentrated on applying machine learning technology to video games, with the aim of both improving existing "artificial intelligence" systems and creating innovative game-play mechanisms which exploit learning techniques. The principle fruit of this research was the Drivatar learning AI system for racing simulation. I developed this (along with Mark Hatton) for the successful Microsoft Xbox title "Forza Motorsport", which shipped in May 2005.

Some relevant links:

• My relevance vector machine page at this site.
• The Drivatar AI and Forza pages at VA GameLabs
• MSR Cambridge
• My old MSR home-page has now disappeared!
• The MLP (machine learning and perception) group pages at MSR

NCRG, Aston University

From 1992 to 1998, I was a member of the Neural Computing Research Group at Aston University. From that time, the following links may still be of some interest:

• 

  The Netlab home page (to which I am a very minor contributor). Netlab is "neural network software" that runs under MATLAB, but in addition to neural nets, also contains many other useful modelling tools. For what its worth, I highly recommend it.

• Probabilistic PCA, and mixtures thereof

  I have received many requests over the last few years concerning the availability of code to implement mixtures of probabilistic principal component analysers [Paper abstract and download]. I've never been able to find time to produce a version of my own, but I did assist with the implementation in Matlab that is available in the aforementioned Netlab toolbox.

• 

  PhiVis is a MATLAB toolbox for visualisation of multivariate continuous data sets, exploiting hierarchical mixtures of probabilistic principal component projections. See the related journal article for further details.

Before Time Began

I moved to the NCRG subsequent to completing a one-year M.Sc. course in "Knowledge-Based Systems" at Edinburgh University (1991-2). My masters thesis was on "Digital Filtering with Recurrent Neural Networks".

Prior to that, I obtained a B.Eng (honours) degree in Electrical and Electronic Engineering at Bristol University, where I spent most of my time playing football.