Dr Charles Day

Title: Lecturer
Phone: 01782 733411
Email: c.r.day@keele.ac.uk
Location: CR110
Role: Computing Third Year Tutor
Contacting me: Student Drop-in Hours
-Mondays: 10am-12pm
-Thursday: 9am-11pm
(Enquiries are also welcome anytime I am in my office)
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My own undergraduate training was in physics and computer science. After graduation I worked in the IT industry supporting manufacturing companies in the telecoms and agricultural sectors of the economy for a number of years. I returned to academia in the early 1990's to complete an MSc and then my PhD (in the field of neural networks). After spells as a post-doctoral researcher at the EC Joint Research Centre in Italy and also in the MacKay Institute for Communication & Neuroscience at Keele, I became a Computer Science lecturer and eventually joined the staff here at Keele in 2001.

Computational modelling and evaluation of human perception: vision, audition, speech processing. Data mining of very large datasets (e.g. astrophysical surveys of the night sky, electromagnetic surveys of the built environment etc.). Intelligent decision support for NHS clinicians trying to identify/treat patients with conditions such as colo-rectal cancer or stroke. Investigator on an EPSRC funded project using neural networks to identify selected chemical elements via their x-ray signatures.

Selected Publications

  • Wootton AJ, Butcher JB, Kyriacou T, Day CR, Haycock PW. 2017. Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX. Engineering Applications of Artificial Intelligence, vol. 64, 152-163. doi> link>
  • Wootton AJ, Taylor SL, Day CR, Haycock PW. 2017. Optimizing Echo State Networks for Static Pattern Recognition. COGNITIVE COMPUTATION, vol. 9(3), 391-399. link> doi>
  • Jabbar SI, Day CR, Heinz N, Chadwick EK, IEEE. 2016. Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images. 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) (pp. 4619-4626). link> doi>
  • Moore HE, Butcher JB, Adam CD, Day CR, Drijfhout FP. 2016. Age estimation of Calliphora (Diptera: Calliphoridae) larvae using cuticular hydrocarbon analysis and Artificial Neural Networks. Forensic Sci Int, vol. 268, 81-91. link> doi>
  • Wootton AJ, Day CR, Haycock PW, IEEE. 2015. An Echo State Network Approach to Structural Health Monitoring. 2015 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). link>

Full Publications List show

Journal Articles

  • Wootton AJ, Butcher JB, Kyriacou T, Day CR, Haycock PW. 2017. Structural Health Monitoring of a Footbridge using Echo State Networks and NARMAX. Engineering Applications of Artificial Intelligence, vol. 64, 152-163. doi> link>
  • Wootton AJ, Taylor SL, Day CR, Haycock PW. 2017. Optimizing Echo State Networks for Static Pattern Recognition. COGNITIVE COMPUTATION, vol. 9(3), 391-399. link> doi>
  • Moore HE, Butcher JB, Adam CD, Day CR, Drijfhout FP. 2016. Age estimation of Calliphora (Diptera: Calliphoridae) larvae using cuticular hydrocarbon analysis and Artificial Neural Networks. Forensic Sci Int, vol. 268, 81-91. link> doi>
  • Day CR, Butcher, JB, Moore, HE, Drijfhout, FP, Adam,CD. 2013. Artificial Neural Network analysis of hydrocarbon profiles for the ageing of Lucilia sericata for Post Mortem Interval estimation. Forensic Science International, vol. 232(1-3), 25-31.
  • Butcher, JB, Day CR, Haycock, PW, Verstraeten, D, Schrauwen, B. 2013. DEFECT DETECTION IN REINFORCED CONCRETE USING RANDOM NEURAL ARCHITECTURES. Computer-Aided Civil and Infrastructure Engineering, 191-207. doi>
  • Butcher JB, Moore HE, Day CR, Adam CD, Drijfhout FP. 2013. Artificial Neural Network analysis of hydrocarbon profiles for the ageing of Lucilia sericata for Post Mortem Interval estimation. Forensic Science International, vol. 232(1-3), 25-31. doi>
  • Butcher, J, Verstaeten, D, Schrauwen, B, Day CR, Haycock, P. 2012. Reservoir computing and extreme learning machines for non-linear time-series data analysis. Neural Networks. doi>
  • Austin JC, Day CR, Kearon AT, Evans DL, Haycock PW. 2010. Comparison method to differentiate between painted objects using polychromatic X-rays. INSIGHT, vol. 52(3), 140-143. link> doi>
  • Austin JC, Day CR, Kearon AT, Haycock PW. 2009. Single element mapping in radiography. X-RAY SPECTROMETRY, vol. 38(6), 492-504. link> doi>
  • Day CR, Austin JC, Butcher JB, Haycock PW, Kearon AT. 2009. Element-specific determination of X-ray transmission signatures using neural networks. NDT & E INTERNATIONAL, vol. 42(5), 446-451. link> doi>
  • Malhotra S, Pandyan AD, Day CR, Jones PW, Hermens H. 2009. Spasticity, an impairment that is poorly defined and poorly measured. Clin Rehabil, vol. 23(7), 651-658. link> doi>
  • Austin JC, Day CR, Kearon AT, Valussi S, Haycock PW. 2008. Using polychromatic X-radiography to examine realistic imitation firearms. Forensic Sci Int, vol. 181(1-3), 26-31. link> doi>
  • Austin JC, Day CR, Kearon AT, Valussi S, Haycock PW. 2008. Characterisation of metallic powder impregnated pastes using polychromatic X-radiography. INSIGHT, vol. 50(10), 550-553. link> doi>

Other

  • Jabbar SI, Day CR, Heinz N, Chadwick EK, IEEE. 2016. Using Convolutional Neural Network for Edge Detection in Musculoskeletal Ultrasound Images. 2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) (pp. 4619-4626). link> doi>
  • Wootton AJ, Day CR, Haycock PW, IEEE. 2015. An Echo State Network Approach to Structural Health Monitoring. 2015 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN). link>
  • Channon A, Aston E, Day C, Belavkin RV, Knight CG. 2011. Critical mutation rate has an exponential dependence on population size. In T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo & R. Doursat (Eds.). Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems (pp. 117-124). Heidelberg: MIT Press. doi>
  • Borg JM, Channon A, Day C. 2011. Discovering and maintaining behaviours inaccessible to incremental genetic evolution through transcription errors and cultural transmission. In T. Lenaerts, M. Giacobini, H. Bersini, P. Bourgine, M. Dorigo & R. Doursat (Eds.). Advances in Artificial Life, ECAL 2011: Proceedings of the Eleventh European Conference on the Synthesis and Simulation of Living Systems (pp. 101-108). Heidelberg: MIT Press. doi>
  • Butcher, J, Verstraeten, D, Schrauwen, B, Day CR, Haycock, P. 2010. Extending reservoir computing with random static projections: a hybrid between extreme learning and RC.
  • Butcher, JB, Verstraeten, D, Schrauwen, B, Day CR, Haycock, PW. 2010. Pruning reservoirs with random static projections.
  • Butcher JB, Lion M, Day CR, Haycock PW, Hocking MJ. 2009. A Low Frequency Electromagnetic Probe for Detection of Corrosion in Steel-Reinforced Concrete. In M. Grantham & C. Majorana (Eds.). Concrete Solutions (pp. 446-451). CRC Press.
  • Lam KP, Austin JC, Day CR. 2007. A coarse-grained spectral signature generator - art. no. 63560S. Eight International Conference on Quality Control by Artificial Vision (vol. 6356, p. S3560). link> doi>
  • Wootton AJ, Day CR, Haycock PW. Echo state network applications in structrual health monitoring. Proceedings of 53rd Annual Conference of The British Institute of Non-Destructive Testing.
  • Butcher JB, Verstaeten D, Schrauwen B, Day CR, Haycock PW. Pruning reservoirs with random static projections. Machine Learning for Signal Processing (MLSP), 2010 IEEE International Workshop on (pp. 250-255).
  • CSC-10033 Natural Computation
  • CSC-20023 Computational Intelligence I