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Dr Martin Wonders

Assistant Professor

Department: Computer and Information Sciences

Martin is a senior lecturer in the department of computer and information sciences and teaches computer vision, applied programming, machine learning, Artificial Intelligent and Robotics. Martin's doctoral thesis on Activity Recognition in monitored environments using utility meter disaggregation, focused on the use of machine learning to both disaggregate signals from utility meters, and use these signals to infer the activity of the occupants.

Martins current research interests focus on Machine and Deep learning using data from a variety of sources including images and video as well as internal and external environmental sensor data from buildings. The latter of which is being applied to energy load demand forecasting for a local architectural company - European Regional Development Fund (ERDF).

Martin Wonders

  • Please visit the Pure Research Information Portal for further information
  • Towards Sparse Rule Base Generation for Fuzzy Rule Interpolation, Tan, Y., Li, J., Wonders, M., Chao, F., Shum, H., Yang, L. 25 Jul 2016, WCCI 2016 - IEEE World Congress on Computational Intelligence
  • Training with synthesised data for disaggregated event classification at the water meter, Wonders, M., Ghassemlooy, Z., Hossain, A. 1 Jan 2016, In: Expert Systems with Applications

  • Elham Mahamedi The Application of AI and Machine Learning for the Better Performance and Predictive Maintenance of Buildings Using Data from Digital Twins Start Date: 08/11/2021
  • Neville Bulmer Intelligent Predictive Maintenance and Energy Load Forecasting for Smart Buildings Start Date: 01/09/2021 End Date: 29/09/2021

  • Computer Science PhD March 02 2017
  • Engineering MSc June 06 2003
  • Computing PGDip June 01 2001
  • Communications Engineering June 30 1997
  • Associate Member Institution of Engineering and Technology (IET) 2014

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