Clotaire Thierry Sanjong Dagang | Automation and Control | Best Researcher Award

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Dr. Clotaire Thierry Sanjong Dagang | Automation and Control | Best Researcher Award

Lecture at University of Dschang/FOTSO Victor University Institute of Technology in Bandjoun, Cameroon.

Dr. Clotaire Thierry Sanjong Dagang is a distinguished lecturer, researcher, and expert in electrical engineering and automation. He holds a Ph.D. in Physics (Electronics) from the University of Dschang, where he now teaches and conducts cutting-edge research in renewable energy automation and control systems. As a key member of the Automation and Signal Processing team, he has significantly contributed to renewable energy integration, control strategies for wind turbine systems, and AI-driven power optimization. His publications in high-impact journals reflect his dedication to advancing energy automation and applied electronics. Dr. Sanjong Dagang is passionate about bridging the gap between theoretical research and practical industrial applications, contributing to the development of sustainable energy solutions.

Publication Profile

Scopus 

Educational Details

  • 2017: Doctorate (Ph.D.) in Physics, specialization in Electronics – University of Dschang
  • 2013: Master of Science in Physics, specialization in Electronics – University of Dschang
  • 2009: Bachelor of Science in Electrical Engineering – IUT-FV of Bandjoun

Professional Experience

Dr. Clotaire Thierry Sanjong Dagang is currently a lecturer in the Electrical Engineering Department at the IUT-FV of Bandjoun, University of Dschang. He has been actively involved in teaching various undergraduate and graduate courses related to electrical engineering, electronics, electrotechnics, and automation. His teaching portfolio includes courses such as Electrical Machines, Electrical Circuits, Measurement Electronics, Simulation of Electrical Systems, and Industrial Electrical Networks and Diagrams.

Before his current full-time role, Dr. Sanjong Dagang served as a part-time lecturer at IUT-FV Bandjoun from 2013 to 2019, where he taught practical and theoretical courses in electronics, electrical engineering, and mechatronics. His extensive experience in academic instruction is complemented by his research activities in automatic control, applied computing, and signal processing, particularly in energy systems automation.

Research Interest

  • Renewable energy systems (wind turbine-based power generation)
  • Control strategies for self-excited induction generators and permanent magnet synchronous generators
  • Fuzzy logic and predictive control in power systems
  • Nonlinear dynamics and stability analysis in electrical circuits
  • Hybrid power systems optimization using artificial intelligence

Author Metrics:

  • Total Publications: 11+
  • Research Areas: Renewable energy, automation, control systems, electrical engineering

Top Noted Publication

Performance Enhancement for Stand-Alone Wind Energy Conversion System Using Super-Twisting Algorithm

Authors: Daniel Borice Tchoumtcha, Clotaire Thierry Sanjong Dagang, and Godpromesse Kenné

Journal: Energy Reports

Volume 13, June 2025

Conclusion

Dr. Clotaire Thierry Sanjong Dagang is a strong candidate for the Best Researcher Award, given his expertise in automation and control of renewable energy systems, his innovative AI-driven research, and his commitment to applied engineering solutions. To further strengthen his candidacy, he could increase international collaborations, expand research output, and secure major research grants in renewable energy automation.

 

 

Ahmed Awad | Control Engineering | Best Researcher Award

Posted on by Best Paper Award

Dr. Ahmed Awad | Control Engineering | Best Researcher Award

Senior Electrical Maintenance Engineer at SESCO TRANS Company, Egypt

Summary:

Dr. Ahmed Awad is an accomplished electrical and control systems engineer with a blend of academic achievements and practical engineering expertise. His work integrates advanced control system algorithms and IoT-driven solutions to enhance the operational efficiency of logistic equipment. Dr. Awad is committed to the seamless fusion of theoretical research and hands-on engineering practice, contributing to innovative advancements in industrial control technologies.

Professional Profile:

👩‍🎓Education:

Dr. Ahmed Awad has a robust academic foundation in Control Engineering. He completed his Bachelor’s degree at Banha University in 2013, graduating with honors and an impressive project on Building Automation Systems, where he led the team to achieve an “Excellent” grade. He proceeded to Mansoura University, obtaining a Preliminary Master’s degree with a grade of “Very Good” in 2014, followed by a Master’s degree in Computer & Automatic Control Engineering in 2018. Dr. Awad is currently registered for his Ph.D. at Mansoura University as of July 2020, continuing his pursuit of advanced research in his field.

🏢 Professional Experience:

With over eight years of extensive experience, Dr. Awad has served as a Senior Electrical Maintenance Engineer at Sesco Trans for Developed Logistics since May 2015. In this role, he has expertly managed the maintenance, troubleshooting, and repair of various logistics heavy equipment, including mobile harbor cranes, loaders, excavators, forklifts, and trucks. His work encompasses designing and maintaining control circuits, programming PLCs (Simatic S5/S7, LS Master K), and handling motor drives such as Siemens SIMOREG and Parker SSD drives. Dr. Awad’s proficiency extends to installing, commissioning, and repairing electronic circuit boards, as well as training new engineers in electrical concepts and maintaining foundational knowledge in hydraulics and mechanical systems.

Research Interests:

Dr. Awad’s research centers on enhancing automation and control systems with a focus on applying algorithms for performance optimization. He has a keen interest in integrating IoT frameworks and deep learning methodologies for monitoring and controlling industrial systems, particularly in the context of logistics and heavy equipment. His work also delves into algorithm-based motor control systems and quality control for logistics applications.

Author Metrics:

Dr. Awad’s publications have been recognized for their relevance in the engineering and computer science communities, contributing to discussions on motor control algorithms, IoT applications, and logistics automation solutions.

Top Noted Publication:

Enhancing Tracking Performance Parameters of Induction Motor Based on PI-PSO Algorithm

  • Authors: M. M. Abd-Elsalam, M. S. Elkasas, S. F. Saraya, A. H. Awad
  • Journal: International Journal of Scientific & Engineering Research
  • Year: 2017
  • Summary: This research investigates the performance improvement of induction motors using a Proportional-Integral (PI) controller optimized with a Particle Swarm Optimization (PSO) algorithm. The study addresses the limitations of conventional PI controllers and demonstrates how integrating PSO enhances the dynamic performance of induction motors, focusing on improved tracking parameters and reduced steady-state error.

IoT Based Framework for Monitoring and Controlling Movable Harbor Cranes

  • Authors: A. H. Awad, M. S. Saraya, M. S. M. Elksasy, Amr M. T. Ali-Eldin
  • Conference: 2021 International Mobile, Intelligent, and Ubiquitous Computing Conference (MIUCC), IEEE
  • Year: 2021
  • Summary: This paper presents an Internet of Things (IoT) framework designed for the real-time monitoring and control of movable harbor cranes. The system aims to enhance operational efficiency and reduce human intervention by utilizing IoT-based sensors and controllers. The proposed framework demonstrates improvements in data collection, crane performance, and remote control capabilities.

A Quality Control System for Logistic Ports Goods Movable Harbor Cranes Based on IoT and Deep Learning

  • Authors: A. H. Awad, M. S. Saraya, M. S. M. Elksasy, Amr M. T. Ali-Eldin, M. M. Abd-Elsalam
  • Journal: Indonesian Journal of Electrical Engineering and Computer Science
  • Year: 2024
  • Summary: This study develops a quality control system for logistics ports, focusing on the operation of movable harbor cranes. The system leverages IoT technology combined with deep learning algorithms to monitor and ensure the safe and efficient handling of goods. The approach enhances fault detection and predictive maintenance, contributing to a more reliable and automated port management system.

Conclusion:

Dr. Ahmed Awad’s unique combination of practical engineering expertise and applied research in control systems and IoT positions him as a strong candidate for the Best Researcher Award. His work on optimizing control algorithms and integrating deep learning for enhanced system performance demonstrates significant potential for continued contributions to the field. To maximize his impact, expanding his research collaborations and publication reach would further cement his status as a leader in control engineering. Overall, Dr. Awad exemplifies the qualities of a dedicated researcher who merges innovation with real-world engineering challenges.