Mutiu Shola | Electrical Engineering | Best Researcher Award

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Dr. Mutiu Shola | Electrical Engineering | Best Researcher Award

Kampala International University, Uganda

Dr. Bakare Mutiu Shola is a dedicated academic and researcher in the field of Electrical and Electronics Engineering. He holds a Ph.D. from Kampala International University, Uganda, an M.Eng. from the University of Ilorin, Nigeria, and a B.Eng. from the Federal University of Technology, Minna. His expertise spans renewable energy, smart grids, load forecasting, high-voltage technology, artificial intelligence, and power systems. With a rich background in both industry and academia, Dr. Bakare has contributed significantly through high-impact research publications in top-tier journals and active teaching roles in higher institutions.

Publication Profile 

Scopus

Orcid

Educational Background 🎓

  • Ph.D. in Electrical and Electronics Engineering
    Kampala International University, Uganda (2022 – 2025)

  • Master of Engineering (M.Eng.) in Electrical and Electronics Engineering
    University of Ilorin, Nigeria (2017 – 2021)

  • Bachelor of Engineering (B.Eng.) in Electrical and Computer Engineering
    Federal University of Technology, Minna, Nigeria (2008 – 2014)
    Graduated with Second Class Upper Division

Professional Experience 💼

  • Assistant Lecturer
    Department of Electrical and Electronics Engineering, Kampala International University, Uganda
    (2022 – Present)
    Courses taught include Power Electronics, Power Quality Management, Circuit Theory, and Electrical Installation & Maintenance.

  • Research Assistant
    Advanced Power and Green Energy Research Group (APGER), University of Ilorin, Nigeria
    (2019 – 2022)

  • Physics & Mathematics Tutor
    Government Day Secondary School, Nigeria
    (2018 – 2019)

  • Site Engineer
    Thamar Engineering Company Ltd, Nigeria
    (2015 – 2018)
    Responsibilities included transformer installation, lighting, and generator setup.

Research Interests 🔬

  • Renewable Energy Systems

  • Energy Management

  • Load Forecasting

  • Smart Grid Technologies

  • Electrical Power System Optimization

  • Artificial Intelligence Applications in Power Systems

Awards and Honors🏆✨

  • Multiple Q1 and Q2-ranked journal publications in high-impact engineering journals such as Scientific Reports, Results in Engineering, Energy Reports, and Energy Conversion and Management: X.

  • Active participation in IEEE academic workshops and international conferences such as ICASSP 2020.

Conclusion🌟

Dr. Bakare Mutiu Shola is a rising scholar in electrical engineering with a strong background in both practical engineering and academic research. His consistent record of publications, academic service, and technical expertise in emerging power systems reflects his commitment to driving innovation in sustainable and intelligent energy solutions. With a future-focused mindset, Dr. Bakare is poised to make continued contributions to both academia and the global energy sector.

Publications 📚

  • 🧠 Comparative Evaluation of Different Fuzzy Tuning Rules on Energy Management Systems Cost Savings
    Ibrahim, O., Bakare, M. S., et al.
    📝 Results in Engineering (2025) – Q1 Journal

  • ☀️ Revolutionizing Solar Power: Enhancing Solar Power Efficiency with Hybrid GEP-ANFIS MPPT under Dynamic Weather Conditions
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Scientific Reports (2025) – Q1 Journal

  • ⚙️ Energy Management Controllers: Strategies, Coordination, and Applications
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Energy Informatics 7(1), 57 (2024) – Q2 Journal

  • 🔋 Predictive Energy Control for Grid-Connected Industrial PV-Battery Systems using GEP-ANFIS
    Bakare, M. S., Abdulkarim, A., et al.
    📝 e-Prime – Advances in Electrical Engineering, Electronics and Energy (2024) – Q1 Journal

  • 📈 A Hybrid Long-Term Industrial Electrical Load Forecasting Model Using Optimized ANFIS with Gene Expression Programming
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Energy Reports 11, 5831–5844 (2024) – Q2 Journal

  • 💡 A Comprehensive Overview on Demand Side Energy Management Towards Smart Grids: Challenges, Solutions, and Future Direction
    Bakare, M. S., Abdulkarim, A., et al.
    📝 Energy Informatics 6(1), 1–59 (2023) – Q2 Journal

  • 🔧 Development of Fuzzy Logic-Based Demand-Side Energy Management System for Hybrid Energy Sources
    Ibrahim, O., Bakare, M. S., et al.
    📝 Energy Conversion and Management: X (2023) – Q1 Journal

  • 🔄 Simulation-Based Testing and Performance Investigation of Induction Motor Drives using MATLAB Simulink
    Makinde, K. A., Bakare, M. S., et al.
    📝 SN Applied Sciences 5(3), 73 (2023) – Q2 Journal

  • 🔍 Performance Evaluation of Different Membership Functions in Fuzzy Logic-Based Short-Term Load Forecasting
    Ibrahim, O., Bakare, M. S., et al.
    📝 Pertanika Journal of Science and Technology (2020) – Q3 Journal

 

 

 

Manas Ranjan Sethi | ECE | Best Researcher Award

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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 : 

Scopus

 

🎓 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.