Machine Learning

Aspects of machine learning which particularly interest me include -

Artificial Immune Systems

PhD student, Adil Ibrahim is undertaking research into new algorithms for negative and clonal selection and immune network theory. We hope to utilise his work in pervasive systems in general and speckled computing systems in particular.

Artificial Neural Networks

This is an area of long-standing interest for me in which I have supervised a number of PhD students, looking at applications such as authorship determination with time-delayed neural networks (Lawrence Thirkell), radio signal classification and novelty detection with associative networks (Alex Iversen), diagnosis of eye disorders with multi-layer perceptrons (Saira Butt) and hybrid approaches to machine learning using genetic algorithms to evolve new neural network architectures (Dave Edwards). Currently PhD student Sarah Gallacher is investigating the use of associative networks in dynamic incremental learning of personal preferences in pervasive systems.

Evolutionary Computing

PhD student Steve Gill is investigating the use of Genetic Algorithms for discovering interesting rules in large data sets. Dave Edwards' PhD looked at the use of evolutionary computing techniques to create a diverse range of new neural network architectures

Swarm Intelligence

PhD student Mohd Mohammad has demonstrated the use of Ant Colony Optimisation techniques in mobile robot path planning.