Adam Wootton

Title: FY Teaching Fellow
Phone: +44 (0)1782 733593
Email: a.j.wootton@keele.ac.uk
Location: Colin Reeves CR37
Role: FY Tutor
Contacting me: By email
Adam Wootton

I first arrived at Keele University in 2009 as an undergraduate student and in 2012 graduated with a first class dual honours degree in Physics and History. When I finished my degree, I began to work for Keele as a casual researcher, during which time I performed a mapping study for a major British natural gas company and acting as a technical consultant for SciCorr, a company concerned with the detection of corrosion by magnetic flux leakage. It was at this time that I began my association with the Foundation Year, initially demonstrating in Maths and Physics modules but subsequently changing my PhD mode of attendance to part time in order to take on more teaching duties. In March 2013 I began my PhD research and in March 2017 I was appointed to the post of Teaching Fellow (Mathematics/Computing/Physics).

While my day-to-day work is now principally concerned with the sciences, I maintain a keen interest in history, and will talk for hours about Staffordshire in the high middle ages if given the opportunity.

My PhD research is centred around the application of a particular recurrent neural network technique, the Echo State Network, to process heterogeneous data arising from non-destructive testing and structural health monitoring. This effectively means that I take data from lots of different types of sensors and teach a computer to process it in order to find out if a structure, usually a bridge or reinforced concrete road, is damaged in some way. This research began in 2013, and my thesis was submitted for examination in the summer of 2017.

Outside of my PhD research, I have continued to look at interesting applications of Echo State Networks in other domains, such as the remote detection of invasive plant species through spectroradiometry and the detection of lung cancer using volatile organic compounds.

Selected Publications

  • Butcher JB, Rutter AV, Wootton AJ, Day CR, Sule-Suso J. 2017. Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. In F. Chao, S. Schockaert & Q. Zhang (Eds.). Proceedings of the 17th Annual UK Workshop on Computational Intelligence (vol. 650, pp. 183-190). Springer. full text>
  • 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. link> doi> full text>
  • 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> full text>
  • 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 text>
  • 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.

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. link> doi> full text>
  • 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> full text>

Other

  • Butcher JB, Rutter AV, Wootton AJ, Day CR, Sule-Suso J. 2017. Artificial Neural Network Analysis of Volatile Organic Compounds for the detection of lung cancer. In F. Chao, S. Schockaert & Q. Zhang (Eds.). Proceedings of the 17th Annual UK Workshop on Computational Intelligence (vol. 650, pp. 183-190). Springer. full text>
  • 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 text>
  • 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.

Teaching involvement in current modules:

Foundation Year Modules

FYO-00096 Computers and Programming

FYO-00120 Computational Thinking

FYO-00122 Decisions, Investigations and Problems