Ms. Veronica Ngunzi | Engineering | Best Researcher Award

Tutorial Fellow at Kenyatta University, Kenya

Veronica Kavila Ngunzi is an experienced professional and educator with over a decade of expertise in renewable energy systems, energy efficiency, and program management. She has an in-depth understanding of Kenya’s power sector, including energy planning, socio-economic data analysis, and the role of development finance in advancing clean energy access. Her work focuses on sustainable energy solutions for critical sectors such as healthcare and agriculture, integrating technical expertise with community empowerment initiatives. She is skilled in energy auditing, hybrid systems design, and capacity-building programs, making significant contributions to the transition to clean energy in Kenya and beyond.

Publication Profile

Scopus

Orcid

Educational Background 🎓

Ph.D. in Renewable Energy Technology (Ongoing) – Kenyatta University, Nairobi, Kenya (2021 – Present)
Ph.D. in Agricultural Processing Engineering (Ongoing) – Jomo Kenyatta University of Agriculture and Technology (2020 – Present)
M.Sc. in Energy Management – University of Nairobi (2015)
B.Sc. in Agricultural Engineering (Double Degree, Second Class Upper Division) – Jomo Kenyatta University of Agriculture and Technology (2018)
Postgraduate Diploma in Project Management (Upper Credit) – Kenya Institute of Management (2012)
B.Sc. in Biomechanical and Processing Engineering (Second Class Upper Division) – Jomo Kenyatta University of Agriculture and Technology (2009)

Professional Experience 💼

Academic Roles

Tutorial Fellow, Kenyatta University, Department of Energy Technology (2020–Present)
- Teaching and supervising courses in Energy Management, Thermodynamics, and Project Management.
- Leading research on renewable energy solutions for healthcare and community-focused applications.
- Guiding students on projects related to Kenya’s energy sector.

Research & Consulting

Research Assistant, Free Appropriate Sustainability Technology (FAST) Research Group, Western University Canada (2023–2024)
- Conducted research on hybrid renewable energy systems for industrial applications.
- Collaborated with global teams to develop scalable, sustainable clean energy solutions.
Energy Consultant (Freelance) – Kenya (2015–2023)
- Conducted energy audits for industrial and agricultural facilities.
- Designed hybrid renewable energy systems for critical sectors.
- Engaged stakeholders to align energy solutions with national planning goals.

Leadership & Advisory Roles

Mentor, Women in Energy Empowerment, Accelerating Women’s Empowerment in Energy Program (2024 – Ongoing)
- Mentoring women in STEM and renewable energy careers.
- Conducting workshops to promote gender equity in the energy sector.
Technical Advisor & Project Team Leader, Milken-Motsepe Prize in Green Energy (2023)
- Led the implementation of a hybrid solar PV and wind energy system with battery storage.
- Achieved semifinalist recognition for innovative clean energy solutions.
Project Lead, Strathmore Energy Research Centre (SERC) & GIZ (2015–2017)
- Led a bioenergy analysis project for 30 tea factories, identifying energy-saving opportunities.
Trainer, Ministry of Energy Kenya & UNDP (2017)
- Developed and implemented a solar water heating training manual for Kenyan industries.
Researcher, Ministry of Higher Education Science & Technology (2012–2016)
- Conducted research on biogas resource assessment and purification for household applications.

Research Interests 🔬

Renewable energy systems (solar PV, biogas, hybrid systems)
Energy efficiency and sector planning
Sustainable energy solutions for healthcare and agriculture
Socio-economic impacts of clean energy adoption
Gender and community empowerment in energy access

Awards and Honors🏆✨

Semifinalist, Milken-Motsepe Prize in Green Energy (2023)
UNESCO Mentorship Recognition, Accelerating Women’s Empowerment in Energy (2024)
Research Grant Recipient, Free Appropriate Sustainability Technology (FAST) Research Group

Conclusion🌟

Veronica Kavila Ngunzi is a dedicated researcher, educator, and renewable energy specialist committed to advancing sustainable energy solutions in Kenya and beyond. With expertise spanning energy policy, hybrid systems, and socio-economic data analysis, she has played a pivotal role in shaping inclusive and impactful energy transitions. Through research, mentorship, and technical innovation, she continues to drive progress in clean energy accessibility and gender equity in the sector.

Publications 📚

📄 Optimization of economics of biomass fuel mix for boilers in tea processing through response surface methodology
📚 Heliyon (2024-12) | 🏛️ Journal article
🔗 DOI: 10.1016/j.heliyon.2024.e40875
✍️ Contributors: Veronica K. Ngunzi, Christopher L. Kanali, Gareth M. Kituu, Erick K. Ronoh

📄 Modeling, simulation and performance evaluation of a PVT system for the Kenyan manufacturing sector
📚 Heliyon (2023-08) | 🏛️ Journal article
🔗 DOI: 10.1016/j.heliyon.2023.e18823
✍️ Contributors: Veronica Ngunzi, Francis Njoka, Robert Kinyua

📄 Analysis of Energy Cost Savings by Substituting Heavy Fuel Oil with Alternative Fuel for a Pozzolana Dryer: Case Study of Bamburi Cement
📚 American Journal of Energy Engineering (2015) | 🏛️ Journal article
🔗 DOI: 10.11648/j.ajee.20150306.13
📖 ISSN: 2329-1648

Mr. Manas Ranjan Sethi | ECE | Best Researcher Award

Research Scholar at NIT Silchar, India

Manas Ranjan Sethi is a dedicated academic professional currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar, with a strong focus on machine learning applications in fault diagnosis and energy systems. He holds an M.Tech in Electronics & Telecommunication from BPUT, Odisha and has over 12 years of teaching experience, having worked as an Assistant Professor at Gandhi Institute for Technology (GIFT) and as a Lecturer at Koustuv Institute of Self Domain, Bhubaneswar. His research interests include machine learning, signal processing, and sustainable energy systems, particularly in wind turbine diagnostics and emotion recognition using EEG signals. Manas has contributed to numerous journals, conferences, and book chapters, and he has earned distinctions such as qualifying CBSE-UGC NET and GATE. He is also skilled in technical tools, enjoys singing, and has a passion for reading.

Publication Profile :

🎓 Educational Background :

Manas Ranjan Sethi is currently pursuing a Ph.D. in Electronics and Instrumentation Engineering at NIT Silchar (since March 2020). He holds an M.Tech in Electronics & Telecommunication (Specialization in Communication Engineering) from BPUT, Odisha (2012), with a CGPA of 8.20. He completed his B.E. in Electronics & Telecommunication from BPUT, Odisha, in 2006, securing a 62.19%. Additionally, he completed his +2 Science and Matriculation from MP Board, Madhya Pradesh.

💼 Professional Experience :

Manas has a rich academic career spanning over 12 years. He served as an Assistant Professor in the Electronics & Communication Engineering Department at Gandhi Institute for Technology (GIFT), Bhubaneswar, from November 2013 to March 2020. Prior to that, he worked as a Lecturer in the Electronics & Telecommunication Engineering Department at Koustuv Institute of Self Domain, Bhubaneswar, from July 2007 to November 2013. He has a strong foundation in teaching and mentoring students in the field of Electronics and Communication Engineering.

📚 Research Interests :

Manas’s research interests lie in the domains of Machine Learning, Signal Processing, and Fault Diagnosis. His work focuses on vibration signal-based diagnostics and energy extraction using wind turbines. He is passionate about leveraging machine learning techniques for predictive maintenance and condition monitoring. His recent research includes the application of meta-classifiers for diagnosing wind turbine blade faults and exploring emotion recognition through EEG signals.

🏆Achievements & Certifications :

Manas has earned several academic distinctions, including qualifying the CBSE-UGC NET (Electronic Science) in July 2018, and securing GATE scores of 260 (2016) and 218 (2011) in Electronics and Communication. He has also attended and contributed to various seminars, workshops, and short-term courses in fields such as VLSI Design, Microwave Filters, and Adaptive Signal Processing.

📝 Publication Top Notes :

Sethi, M. R., Subba, A. B., Faisal, M., Sahoo, S., & Koteswara Raju, D. (2024). Fault diagnosis of wind turbine blades with continuous wavelet transform based deep learning model using vibration signal. Engineering Applications of Artificial Intelligence, 138, 109372.

Sethi, M. R., Sahoo, S., Dhanraj, J. A., & Sugumaran, V. (2023). Vibration Signal-Based Diagnosis of Wind Turbine Blade Conditions for Improving Energy Extraction Using Machine Learning Approach. Smart and Sustainable Manufacturing Systems, 7(1), 14–40.

Chatterjee, S., Sethi, M. R., & Asad, M. W. A. (2016). Production phase and ultimate pit limit design under commodity price uncertainty. European Journal of Operational Research, 248(2), 658–667.

Sethi, M. R., Parhi, S. S., Sahoo, S., Sugumaran, V., & Mohanty, S. R. (2023). Fault Diagnosis of Wind Turbine Blades Through Vibration Signal Using Filtered Cultivation Data: A Comparative Study. Proceedings of the 2023 IEEE Region 10 Symposium, TENSYMP 2023.

Kar, P., Hazarika, J., & Sethi, M. R. (2023). A Comparative Study between Supervised and Unsupervised Techniques for Two Class Emotion Recognition using EEG. Proceedings of the 2023 IEEE 8th International Conference for Convergence in Technology, I2CT 2023.

Banala, H. S., Sahoo, S., Sethi, M. R., & Sharma, A. K. (2023). Fault Diagnosis in Wind Turbine Blades Using Machine Learning Techniques. In R. Doriya, B. Soni, A. Shukla, & X. Z. Gao (Eds.), Machine Learning, Image Processing, Network Security and Data Sciences (Lecture Notes in Electrical Engineering, Vol. 946), 401–411. Springer, Singapore.

Sethi, M. R., Sahoo, S., Kanoongo, S., & Hemasudheer, B. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Rule Classifier. Proceedings of the 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET 2022), 1–6. doi: 10.1109/ICEFEET51821.2022.9848401.

Sethi, M. R., Hemasudheer, B., Sahoo, S., & Kanoongo, S. (2022). A Comparative Study on Diagnosing Wind Turbine Blade Fault Conditions using Vibration Data through META Classifiers. Proceedings of the 2022 4th International Conference on Energy, Power, and Environment (ICEPE 2022), 1–5. doi: 10.1109/ICEPE55035.2022.9798026.

Veronica Ngunzi | Engineering | Best Researcher Award