Project: Enhanced demand forecasting and leakage detection utilising high-resolution loggers
Supervisors: Professors Memon and Savic, Paul Merchant
Paul recently completed a MSc in Robotics at Plymouth University, with a thesis focusing on human-robot interaction, with the research being published at 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI) in New Zealand, available at:
The research involved using a robot with a projected face and 3 degrees of freedom that could socially interact with people. The research showed that a robot that behaved in a more social way was able to collect more money for charity. During the Master’s at Plymouth, there were two modules that focused on Artificial Intelligence, giving a grounding for the PhD research.
For his undergraduate study, Paul completed a BSc in Computer Science and Philosophy at Keele University, graduating in 2006. This included 6 months study abroad in South Africa. The main dissertation was an Artificial Intelligence that learnt by experience for a board game, Reversi.
Paul worked in industry prior to his Master’s degree, with roles in web development, teaching and network/system administration. Paul enjoyed working in these different areas, but felt like he wanted a bigger challenge, hence the move to return to academia.
Paul is looking forward to getting further involved in his research and hopes that he can provide a useful contribution to the difficult and valuable task of understanding demand and leakage. Paul has a research focus on using machine learning to better understand water demand and leakage. The research is being conducted in conjunction with an industry partner, South West Water, with a wide scope for research into this challenging subject.
• Water demand
• Machine learning
• Big data
• Water distribution
WISE Summer School 2017 Presentation: Paul_Wills_Jun17