Ian is a Visiting Fellow within the School of Computing and Communications in the STEM Faculty, working in the field of applied machine learning.
My research interests include:
I’m particularly interested in applying machine learning techniques to domains which are less accessible to brute force, large dataset, modelling or, where the dataset is niche. For example, where the there is a lack of data and the heuristic needs to become more adaptive to a changing or adaptive data environment. Examples of such an environment would be, climate change science where historical data does not necessarily represent current experience, making it difficult to make predictions from the historical data. Alternatively in the healthcare field where patient centric approaches to healthcare require a more adaptive heuristic approach to deliver more personalised health information back to the clinician.
I’m also interested in the theoretical underpinnings of computation, in particular the implications of the No Free Lunch theorem to NP versus P
Hydrographical Flow Modelling of the River Severn Using Particle Swarm Optimization (2019)
The Computer Journal ((Early Access))
An Evaluation of Performance Enhancements to Particle Swarm Optimisation on Real-World Data (2016-12-14)
PhD thesis The Open University