Definite Term Lecturer and Adjunct Professor

Contact InformationAyman El-Hag

Phone: 519-888-4567 x31431
Location: EIT 4016

Biography Summary

Ayman El-Hag, PhD, SM IEEE, P. Eng., received his Ph.D. degree from the University of Waterloo in 2003. He joined the Saudi Transformer Co. as a Quality Control and testing Engineer from 1993 to 1999. His main duties included the implementation of ISO 9001 provisions and the testing of distribution transformers as per IEC 60076. Currently, Dr. El-Hag is an adjunct professor and lecturer at the University of Waterloo. Dr. El-Hag main area of interest is condition monitoring and diagnostics of electrical insulation. Dr. El-Hag received several funds from NSERC and Qatar foundation that are mainly related to inspection of outdoor ceramic insulators, transformers and design of non-ceramic insulators. The total value of the funds is more than two million Canadian dollars. He published many referred journal and conference papers in the area of monitoring of outdoor insulators and transformers. Dr. El-Hag is a registered engineer in the province of Ontario, a senior member of IEEE, a guest editor for energies special issue “High Voltage Engineering and Application”, was an associate editor for the IEEE Dielectric and Electrical Insulation Transaction (2018-2019) and the middle east editor for the IEEE Insulation magazine (2016-2018). Also, Dr. El-Hag is a member of the IEEE outdoor insulation committee and the IEEE Std 1523 (IEEE Guide for the Application, Maintenance, and Evaluation of Room Temperature Vulcanizing (RTV) Silicone Rubber Coatings for Outdoor Insulation Applications).

Research Interests

  • Condition monitoring and diagnostics of electrical insulation.
  • Partial discharge measurement.
  • Design of electrical insulating materials.
  • Electric stress control.
  • Pulse power technology.
  • Energy management and smart grid.
  • Power system transients
  • Engineering education.


  • 2004, Doctorate, Electrical and Computer Engineering, University of Waterloo
  • 1998, Master of Science, Electrical Engineering, King Fahd University of Petroleum and Minerals
  • 1993, Bachelor of Science (BSc), Electrical Engineering, King Fahd University of Petroleum and Minerals


  • GENE 123 - Electrical Circuits and Instrumentation
    • Taught in 2016, 2019
  • ECE 190 - Engineering Profession and Practice
    • Taught in 2018
  • MTE 482 - Mechatronics Engineering Project
    • Taught in 2019
  • ECE 204 - Numerical Methods
    • Taught in 2019
  • MTE 481 - Mechatronics Engineering Design Project
    • Taught in 2019
* Only courses taught in the past 5 years are displayed.

Selected/Recent Publications

  • Ahmad Nayyar Hassan and Ayman El-Hag, Two-Layer Ensemble-Based Soft Voting Classifier for Transformer Oil Interfacial Tension Prediction, Energies, 13(7), 2020, 1 - 11
  • Amr Ibrahim, Ahmad Dalbah, Ayaat Abualsaud, Usman Tariq and Ayman El-Hag, Application of Machine Learning to Evaluate Insulator Surface Erosion, IEEE Transactions on Instrumentation and Measurement, 2020
  • Daouda Koné, Refat Atef Ghunem, Ladji Cissé, Yazid Hadjadj and Ayman H. El-Hag, Effect of Residue Formed during the AC and DC Dry-Band Arcing on Silicone Rubber Filled with Natural Silica, IEEE Transactions on Dielectrics and Electrical Insulation, 2019
  • Satish Polisetty, Ayman El-Hag and Shesha Jayaram, Classification of Common Discharges in Outdoor Insulation Using Acoustic Signals and Artificial Neural Network, IET High Voltage, 2019
  • Amir Abbas Soltani and Ayman El-Hag, Denoising of Radio Frequency Partial Discharge Signals Using Artificial Neural Network, Energies, 2019
  • Alhaytham Alqudsi and Ayman El-Hag, Application of Machine Learning in Transformer Health Index Prediction, Energies, 2019
  • Abdelrahman K. Abouzeid, Ayman El-Hag and Khaled Assaleh, Equivalent Salt Deposit Density Prediction of Silicone Rubber Insulators under Simulated Pollution Conditions, Electric power components and Systems, 2018
  • Alhaytham Alqudsi and Ayman El-Hag, Assessing the Power Transformer Insulation Health Condition Using a Feature-Reduced Predictor Model, IEEE Transactions on Dielectrics and Electrical Insulation, 2018
  • Kamel Benhmed, Abdelniser Mooman, Abdunnaser Younes, Khaled Shaban and Ayman El-Hag, Feature Selection for Effective Health Index Diagnoses of Power Transformers, Power Engineering Letters, IEEE Transactions on Power Delivery, 2018
  • Ali Wadi, Wasim Al-Masri, Wisal Siyam, Mamoun F. Abdel-Hafez, Ayman H. El-Hag, Accurate Estimation of Partial Discharge Location using Maximum Likelihood, IEEE Sensors Letters, 2017
  • Wei Lee Woon, Zeyar Aung, and Ayman El-Hag, Intelligent Monitoring of Transformer Insulation using Convolutional Neural Networks,, Data Analytics for Renewable Energy Integration. Technologies, Systems and Society,, W. Woon, Z. Aung, A. Catalina & S. Madnick,
  • Ayman El-Hag (Editors), High Voltage Engineering and Appkications, 2020