I work as a Research Software Design Engineer in the machine learning group at Microsoft Research in Cambridge, UK.

My main role is in the development of Infer.NET which is a .NET library for machine learning. It provides state-of-the-art algorithms for probabilistic inference from data. Various Bayesian models such as Bayes Point Machine classifiers, TrueSkill matchmaking, hidden Markov models, and Bayesian networks can be implemented using Infer.NET. I also have a strong interest in using machine learning for ranking.

Before working at Microsoft Research, I spent several years developing Advanced Control software at Aspen Technology. One of the highlights was the development of a fully non-linear Model Predictive Controller (Aspen Apollo) which has been widely adopted in the polymer manufacturing industry. This was made possible by developing a new form of non-linear regression model (a Bounded Derivative Network) which has more natural interpolation and extrapolation properties than a traditional Multi-layer Perceptron model, and which provides guaranteed global behaviours such as montonic responses in specified input variables. A description of Bounded Derivative Networks can be found in 'Introducing the bounded derivative network—superseding the application of neural networks in control', P. Turner, J. Guiver, Journal of Process Control, pages 407–415, 2005

A description of the many practical issues faced in putting a non-linear controller into a large-scale manufacturing plant can be found in 'Experiences with Non-linear MPC in Polymer Manufacturing', Kelvin Naidoo, John Guiver, Paul Turner, Mike Keenan, Michael Harmse in Assessment and Future Directions of Nonlinear Model Predictive Control (Lecture Notes in Control and Information Sciences)

The Aspen Apollo controller was derived from an earlier controller developed at NeuralWare ('A nonlinear industrial model predictive controller using integrated PLS and neural net state-space model', H. Zhao, J. Guiver, R. Neelakantan, L.T. Biegler, Control Engineering Practice, 9, 2001., 'State space nonlinear process modeling: identification and universality' ,G.B. Sentoni, J.P. Guiver, H. Zhao, and L.T. Biegler. AIChE Journal, March 1998).

At NeuralWare (one of the early commercial neural net companies, founded by Casey and Jane Klimasauskas in 1987), I was a principal research engineer and was, for many years, the lead sofware developer, responsible for the design and evolution of the company's neural net products.