Dr. Attique Ur Rehman

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Dr. Attique Ur Rehman

Assistant Professor (IEEE Senior Member & HEC Approved PhD Supervisor)

Doctor of Philosophy; Auckland University of Technology, New Zealand; 2021
Master of Science; RWTH Aachen University, Germany; 2013 
Bachelor of Engineering
; Air University Islamabad, Pakistan; 2009    


Research Interests:
Smart Grids, Energy Efficient Systems, Energy Management, Load Disaggregation, Applied Artificial Intelligence, and Data Science


Data Analytics Engineer; Horizon Energy Group Ltd., New Zealand; 2021 – 2021

Callaghan Innovation R&D Fellow; Genesis Energy Ltd., New Zealand; 2018 – 2021

Researcher; Manukau Institute of Technology, New Zealand; 2019 – 2020

Lecturer; Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Pakistan; 2013 – 2017

Student Assistant; RWTH Aachen University, Germany; 2011 – 2013

Assistant Divisional Engineer; Pakistan Telecommunication Company Ltd., Pakistan; 2009 – 2010


Teaching Experience/Courses Taught

  • AI Applications for Smart Grid
  • Power Distribution and Utilization
  • Power Electronics
  • Power System Operation and Control
  • Linear Circuit Analysis
  • Electronic Devices and Circuits
  • Computer Architecture


Research Publications

Journal Articles
  • A.U. Rehman, T.T. Lie, B. Vallès and S.R. Tito, “Event-Detection Algorithms for Low Sampling Nonintrusive Load Monitoring Systems Based on Low Complexity Statistical Features,” in IEEE Transactions on Instrumentation and Measurement, vol. 69, no. 3, pp. 751-759, March 2020.
  • A.U. Rehman, T.T. Lie, B. Vallès, and S.R. Tito, “Non-Intrusive Load Monitoring of Residential Water-Heating Circuit Using Ensemble Machine Learning Techniques,” Inventions, vol. 5, no. 4, p. 57, 2020.
  • A.U. Rehman, T.T. Lie, B. Vallès, and S.R. Tito, “Non-Invasive Load-Shed Authentication Model for Demand Response Applications Assisted by Event-Based Non-Intrusive Load Monitoring,” Energy and AI, vol. 3, p. 100055, 2021.
  • A.U. Rehman, T.T. Lie, B. Vallès and S.R. Tito, “Comparative Evaluation of Machine Learning Models and Input Feature Space for Non-Intrusive Load Monitoring,” in Journal of Modern Power Systems and Clean Energy, doi: 10.35833/MPCE.2020.000741.
Conference Papers
  • A.U. Rehman, T.T. Lie, B. Vallès and S.R. Tito, “Low Complexity Event Detection Algorithm for Non-Intrusive Load Monitoring Systems,” 2018 IEEE Innovative Smart Grid Technologies – Asia (ISGT Asia), 2018, pp. 746-751.
  • A.U. Rehman, T.T. Lie, B. Vallès and S.R. Tito, “Low Complexity Non-Intrusive Load Disaggregation of Air Conditioning Unit and Electric Vehicle Charging,” 2019 IEEE Innovative Smart Grid Technologies – Asia (ISGT Asia), 2019, pp. 2607-2612.
  • A.U. Rehman et al., “Applications of Non-Intrusive Load Monitoring Towards Smart and Sustainable Power Grids: A System Perspective,” 2019 29th Australasian Universities Power Engineering Conference (AUPEC), 2019, pp. 1-6.
  • A.U. Rehman, S.R. Tito, D. Ahmed, P. Nieuwoudt, T.T. Lie and B. Vallès, “An Artificial Intelligence-Driven Smart Home Towards Energy Efficiency: An Overview and Conceptual Model,” 2020 FORTEI-International Conference on Electrical Engineering (FORTEI-ICEE), 2020, pp. 47-52.
  • A.U. Rehman et al., “Non-Intrusive Load Monitoring: A Computationally Efficient Hybrid Event Detection Algorithm,” 2020 IEEE International Conference on Power and Energy (PECon), 2020, pp. 304-308.
  • I. Anwar, M. O. Mohsin, S. Iqbal, Z. U. Abideen, A.U. Rehman and N. Ahmed, “Design and fabrication of an underwater remotely operated vehicle (Single thruster configuration),” 2016 13th International
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