School of Life Sciences

I’ve been fascinated in computers since a very young age when I first got my hands on my Dad's Commadore 64 which these days, feels like a lifetime ago! Since then I’ve developed a huge interest in Computational Intelligence and the many techniques which it involves. My PhD investigated the use of Artificial Neural Networks (more specifically Reservoir Computing - see Research tab) when applied to highly non-linear time-series datasets.  A secondary aim of this research was the automatic detection of defects within reinforced concrete.  Since completing my PhD I am eager to pursue my interest in understanding how the brain works, hence I'm currently in the process of moving into Computational Neuroscience in my spare time and have recently taken up a post doctoral position in Neuroscience.

I graduated from Keele University with a BSc in Computer Science and Management Science in 2007. During that time I was involved in a Nuffield bursary funded summer project investigating the use of structured abstracts within Software Engineering. For my final year project I studied L-Systems and created a program which modelled the growth of trees using axioms and growth rules. This is still an ongoing project now as I have many things to work on to get the program to the stage I want. During the summer between graduation and the start of my PhD I was involved in a project which used a Self Organising Map to classify X-Ray signatures of metals with promising results.

Here's my Linkedin profile for those interested.

My interests lie in the huge fields of Computational Intelligence, especially anything to do with Neural Networks, particularly the recently new area of Reservoir Computing and Echo State Networks.  A good introduction on Echo State Networks can be found on Scholarpedia. A free Matlab and Python toolkit, along with many publications using Reservoir Computing can be found on the Reservoir Lab website which is based at Ghent University, Belgium: http://reslab.elis.ugent.be/.

My other research interests lie in biologically plausible approaches at replicating how the brain functions, such as spiking neural networks and the fascinating field of Computational Neuroscience.  Other interests that I have worked on include speech recognition, signal processing (including recent studies into stem cell classification), robotics and generally finding out as much as I can on how the human brain works.  To further my knowledge for this field, I have attended several excellent 
summer schools on Computational Neuroscience including the course at the University of Ottawa, Canada (for more info see http://www.neurodynamic.uottawa.ca/summer.htm), CRCNS summer school (https://crcns.org/course/), CoSMo 2012 (http://www.compneurosci.com/CoSMo2012/) and the IBRO/UNESCO Interregional summer school on Computational Neuroscience in Hyderabad, India (IBRO summer school).  While intensive, these courses were very interesting where several topics regarding neural models, analysis of neural data and stochastic resonance, among others, were covered. 

I recently took a step towards following my interest in the brain and understanding more about its functionality by starting a post doc at Keele in Neuroscience where I am part of a project that investigates plasticity models in the brain: an area of great interest in discovering how the brain works.

I'm also working with colleagues in the department on biologically inspired models for robot navigation for which several papers have been published (see Publications tab).

• Butcher, J.B., Verstraeten, D., Schrauwen, B., Day, C.R. and Haycock, P.W., 2013, "Defect detection in reinforced concrete using Reservoir Computing and Extreme Learning Machines", in press
• Butcher, J.B., Moore, H.E., Day, C.R., Adam, C.D., and Drijfhout, F.P., 2013, "Artificial neural network analysis of hydrocarbon profiles for the ageing of Lucilia sericata for post mortem interval estimation", Forensic Science International, 232(1-3): 25-31
• Butcher, J.B., Verstraeten, D., Schrauwen, B., Day, C.R. and Haycock, P.W., 2013, "Reservoir computing and extreme learning machines for non-linear time series data analysis", Neural Networks, 38: 76-89
• Kyriacou, T.K., Butcher, J.B., and Day, C.R., 2011, "A biologically inspired model of the head direction system of rats implemented on a robot",  International Workshop on Evolutionary and Reinforcement Learning for Autonomous Robot Systems (ERLARS) 2011
• Butcher, J.B., Verstraeten, D., Schrauwen, B., Day, C.R. and Haycock, P.W., 2010, "Pruning reservoirs with random static projections", IEEE workshop on Machine Learning for Signal Processing (MLSP)
• Butcher, J., Verstraeten, D., Schrauwen, B., Day, C. and Haycock, P., 2010, "Extending reservoir computing with random static projections: a hybrid between extreme learning and RC", European Symposium on Neural Networks (ESANN)
• Butcher, J.B., Lion, M., Day, C.R., Haycock, P.W., Hocking, M.J., Bladon, S., 2009, "A Low Frequency Electromagnetic Probe for Detection of Corrosion in Steel-Reinforced Concrete", In Grantham, M., Majorana, C. and Valentina, S. (eds), Concrete Solutions , pages 417-424, CRC Press
• Day, C.R., Austin, J.C., Butcher, J.B., Haycock, P.W., Kearon, A.T., 2009, "Element-specific determination of X-ray transmission signatures using neural networks", NDT&E International, 42(5): 446-451
• Kitchenham B.A., Brereton O.P., Owen S.C., Butcher J. and Jefferies C., 2008, "Length and readability of structured software engineering abstracts", IET Software, 2(1): 37-45