Dr. Fei Long | Power Systems | Most Cited Article Award

Posted on by Computer Scientists Awards

Dr. Fei Long | Power Systems | Most Cited Article Award

Lecturer, China Three Gorges University, China

Dr. Fei Long is a dedicated Lecturer and Postdoctoral Researcher at the School of Electrical Engineering and New Energy, China Three Gorges University 🇨🇳. With a deep-rooted passion for systems control and stability, he has significantly contributed to the advancement of control theory, especially in time-delay and power systems. Known for his academic rigor and innovation, Dr. Long is actively engaged in top-tier research that addresses critical challenges in modern power systems. 📊🔋

Publication profile

Scopus

🎓 Education Background

Dr. Long earned his Ph.D. in Control Science and Engineering from China University of Geosciences (Wuhan) 🎓 between September 2016 and June 2022. Prior to this, he completed his undergraduate studies in Electrical Engineering and Automation at Hubei University of Technology from 2011 to 2015 ⚡📚.

💼 Professional Experience

Since June 2022, Dr. Fei Long has been serving as a Lecturer and Postdoctoral Researcher at China Three Gorges University. His role involves both teaching and conducting cutting-edge research in the field of electrical engineering and control systems. 🏫🔍

🏆 Awards and Honors

Dr. Long is the Principal Investigator of a National Natural Science Foundation of China (Youth Science Fund Project) 🧪. Notably, two of his research papers have been recognized as ESI Highly Cited Papers, placing them in the top 1% of citations worldwide 🌍📈—a testament to the global impact of his research.

🔬 Research Focus

Dr. Long’s primary research interests lie in the stability and robust control of time-delay systems and power systems ⏳⚙️. His work emphasizes innovative mathematical modeling and control strategies to enhance system resilience and performance, particularly in neural networks and energy systems integration.

✅ Conclusion

With a robust academic background, impactful research contributions, and a strong focus on systems stability, Dr. Fei Long stands out as a prominent young researcher in the field of electrical and control engineering. His commitment to excellence and scholarly achievement continues to inspire and shape the future of sustainable energy systems. 🚀📘

📚 Top Publication Notes

IEEE Transactions on Cybernetics (2022) Highly cited paper, recognized for its innovation in delay systems control (Cited by 100+ articles).

IEEE Transactions on Neural Networks and Learning Systems (2023) – Advanced delay-product-type functionals (Cited by 80+ articles).

Automatica (2020) – A key contribution to relaxed matrix inequalities (Cited by 120+ articles).

IEEE Transactions on Systems, Man, and Cybernetics: Systems (2021) – Used in applied power systems and neural networks (Cited by 90+ articles).

Applied Mathematics and Computation (2019) –  Mathematical advancements in delay control theory (Cited by 85+ articles).

IEEE Transactions on Cybernetics (2024) –  Recent breakthrough in delayed neural networks stability.

Assoc. Prof. Dr. CHEN CAO | electric engineering | Best Researcher Award

Posted on by Computer Scientists Awards

Assoc. Prof. Dr. CHEN CAO | electric engineering | Best Researcher Award

Shenyang University of Technology, China

Dr. Cao Chen is an esteemed Associate Professor at the School of Electrical Engineering, Shenyang University of Technology. He serves as a Doctoral and Master Supervisor, contributing significantly to electrical engineering research and education. With expertise in power transformers, switchgear, and electrical equipment diagnostics, he has led multiple national and provincial-level research projects, published over 50 research papers, and holds 30 authorized patents. His contributions to science and technology have earned him numerous prestigious awards, including multiple first prizes in scientific and technological progress from the Liaoning Provincial Government and China Machinery Industry Federation.

Publication Profile

Scopus

🎓 Education & Experience:

Dr. Cao Chen completed his postdoctoral research at Shenyang University of Technology between 2018 and 2020. He then transitioned to academia, first as a Lecturer (2020-2021) and later as an Associate Professor (2021-present) at the School of Electrical Engineering, Shenyang University of Technology. His extensive teaching portfolio includes undergraduate and postgraduate courses on electrical engineering, switchgear disconnection technology, and energy and power engineering.

🏆 Awards and Honors:

Dr. Cao Chen has received numerous prestigious awards, including the Liaoning Provincial Science and Technology Progress Second Prize (2024, First Completer) and First Prize (2019) for advancements in transformer performance enhancement and switchgear flexibility. Additionally, he has won China Machinery Industry Science and Technology First Prizes (2016, 2024) for his pioneering work in high-voltage switching and overvoltage suppression technologies. He is also actively involved in IEEE PES Power Interruption Technical Committee (China) and multiple committees of the China Electrotechnical Society.

🔬 Research Focus:

Dr. Cao Chen’s research revolves around transformer diagnostics, power equipment reliability, and fault detection. His work focuses on developing advanced online monitoring and fault diagnosis techniques for power transformers using vibration-based methods and multi-source data fusion. He has spearheaded multiple projects funded by the National Natural Science Foundation of China, provincial departments, and corporate enterprises, driving innovation in power system reliability.

🔚 Conclusion:

Dr. Cao Chen is a pioneering researcher and educator in electrical engineering, particularly in power equipment diagnostics and fault analysis. His groundbreaking work in transformer monitoring, fault detection, and power system reliability has earned him national and international recognition. As a leader in scientific research, a dedicated professor, and a key contributor to industrial advancements, he continues to push the boundaries of electrical engineering through innovative solutions and impactful research. 🚀

📖 Publications:

State Diagnosis Method of Transformer Winding Deformation Based on Fusing Vibration and Reactance Parameters. IET Electric Power Applications. (Cited in SCI Zone 2)

Research on Simulation Analysis and Joint Diagnosis Algorithm of Transformer Core-Loosening Faults Based on Vibration Characteristics. Energies. (Read here)

Transformer winding mechanical state diagnosis method based on current-frequency-vibration parameters. Journal of Electric Machines and Control.

Magnetostrictive vibration model and loose fault diagnosis method of transformer core based on elastic mechanics-thermodynamics. High Voltage Technology.

Monitoring Method on Loosened State and Deformational Fault of Transformer Winding Based on Vibration and Reactance Information. IEEE ACCESS. (Cited in SCI Zone 1)