• Electrical Machines and Drives
• High Voltage Engineering
• Electrical Insulation Materials
• Power Transformer Diagnostics
• Power Systems Engineering
• Partial Discharge Detection and Localization
• Acoustic Signal Processing
• Time Reversal Modelling
• Artificial Intelligence in Power Systems
• Machine Learning and Mathematical Modelling
• Deep Learning for Condition Monitoring
• Renewable Energy and Smart Grids

1. Sekatane, P., Jordaan, J., & Bokoro, P. (2019). Assessment of moisture content in power transformers based on traditional techniques and an adaptive neuro-fuzzy inference system. 11th International Conference on Electrical and Electronics Engineering (ELECO), Bursa, Turkey, pp. 987–991.
2. Sekatane, P., Jordaan, J., & Bokoro, P. (2019). A review of detection and mitigation of negative dissipation factors in high voltage power transformers. IEEE AFRICON International Conference, Accra, Ghana.
3. Sekatane, P. M., & Olwal, T. O. (2021). Residual life estimation of power transformers based on Karl Fischer analysis and an adaptive neuro-fuzzy inference system. IEEE AFRICON 2021.
4. Sekatane, P., & Bokoro, P. (2021). Improving diagnostic techniques of moisture content in power transformers using an adaptive neuro-fuzzy inference system. IEEE PowerAfrica 2021.
5. Sekatane, P. M. (2023). The actual operating lifespan of power transformers based on traditional techniques and adaptive neuro-fuzzy inference systems. IEEE PES/IAS PowerAfrica Conference, Marrakech, Morocco.
   https://doi.org/10.1109/PowerAfrica57932.2023.10363304
6. Sekatane, P. M., & Bokoro, P. (2023). Time reversal vs. integration of time reversal with convolutional neural networks in diagnosing partial discharge in power transformers. Energies, 16(23), 7872.
   https://doi.org/10.3390/en16237872
7. Sekatane, P. M., & Bokoro, P. (2023). Partial discharge localization through k-NN and SVM. Energies, 16(21), 7430.
   https://doi.org/10.3390/en16217430

• Professional Engineering Technician (Pr.Techni Eng) – Engineering Council of South Africa (ECSA,2018)
• UCDG Grant Recipient (2025) – Staff Replacement Grant
• UCDG Grant Recipient (2024) – Harvard Higher Education Teaching Certificate Programme
• Contributor to peer-reviewed international journals in electrical power and energy engineering
• Participant in Sector Education and Training Authority (SETA) skills development and Work Integrated Learning (WIL) programmes (EWSETA, MERSETA, ETDP SETA, CHIETA and etc)

Current research projects include but not limited:

• Machine Learning-Based Partial Discharge Detection in Power Transformers
• Integration of Time Reversal Modelling with Convolutional Neural Networks for PD Localization
• Advanced Signal Processing Techniques for Transformer Fault Diagnostics
• Artificial Intelligence-Driven Condition Monitoring for High Voltage Power Equipment

These projects aim to develop intelligent diagnostic systems for power infrastructure, supporting reliability, predictive maintenance, and improved asset management in modern energy networks.

Dr. Permit Mathuhu Sekatane is a distinguished Professional Engineering Technician (Pr Techni Eng) with over a decade of experience bridging the gap between high-level academic research and heavy-duty industrial application. He holds a PhD and an MPhil in Electrical and Electronic Engineering from the University of Johannesburg, complemented by a Higher Education Teaching Certificate from Harvard University, including Assessor, Moderator and facilitator certificates from Turnstone training solutions. His technical foundation is equally robust, supported by a National Diploma and BTech from the Tshwane University of Technology (TUT), along with an electrical Trade Test, and a three-phase Wireman’s License.

Dr. Sekatane’s career began at Powertech Transformers, where he rose from a Trainee to a Senior Commissioning Technician, gaining deep expertise in transformer installation, switchgear servicing, and protection systems. In 2016, he transitioned into academia at TUT, where he served as a Laboratory Technologist and Faculty SHE Representative. In this role, he manages technical infrastructure, oversees occupational health and safety (SHEQ) compliance, and supervises research in fields such as machine learning for partial discharge localization and energy efficiency.

Furthering his contribution to higher education, Dr. Sekatane is appointed as an Adjunct Academic Lecturer in the Department of Electrical and Smart Systems Engineering within the College of Science, Engineering and Technology (CSET) at the University of South Africa (UNISA). Beyond his academic duties, he remains deeply embedded in industry as a Technical Engineer at Setjhaba CET, where he maintains critical Gautrain infrastructure during specialized maintenance windows. He is a certified SAPVIA PV GreenCard holder and a graduate of the SuperSolarSchool, reflecting his commitment to the renewable energy sector.

His leadership extends to financial and project management; in 2023 alone, he successfully oversaw more than R6 million in SETA-funded training projects, including Solar PV and Work Integrated Learning programs. A strategic thinker with a hands-on approach, Dr. Sekatane is recognized for his collaborative nature and dedication to engineering excellence. He is a published researcher who has presented at international conferences such as IEEE AFRICON and serves as a peer reviewer for high-impact journals. Driven by integrity and a passion for mentorship, he leverages his unique blend of academic insight and technical skill to advance both engineering education and large-scale infrastructure projects.