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)

Dr. IDRISS DAGAL | Electrical Engineering | Best Researcher Award

Assistant Professor, Istanbul Beykent University, Turkey

Dr. Idriss Dagal, an Assistant Professor at Istanbul Beykent University, is a researcher and engineer from Chad specializing in Electrical Engineering, Renewable Energy, and Artificial Intelligence. With a career spanning over a decade, he has worked in various roles, including Aircraft Engineer and Lecturer, and has contributed extensively to the field of electrical systems, power electronics, and optimization algorithms. His academic journey includes a Ph.D. from Yıldız Technical University, Istanbul, Turkey, where he also completed his MSc in Avionics Engineering. Dr. Dagal has authored over 30 publications and is an active reviewer for renowned journals. 🌍💡

Publication Profile

ORCID

Education:

Dr. Dagal holds a Bachelor of Science (B.S.) degree in Industrial and Maintenance Engineering from Mongo Polytechnic University (Chad, 2006), a Master of Science (M.Sc.) in Aviation Engineering from Ethiopian Airlines Aviation School (Ethiopia, 2010), and a Ph.D. in Electrical Engineering from Yıldız Technical University (Turkey, 2022). He is currently pursuing a second M.Sc. in Avionics Engineering at Yıldız Technical University. 🎓📚

Experience:

Dr. Dagal’s professional experience spans multiple countries and roles, including serving as an Aircraft Maintenance Engineer in Chad, a Lecturer at various institutions in Chad, and a Sales Engineer in Turkey. Since 2024, he has been serving as an Assistant Professor at Istanbul Beykent University, Turkey, specializing in electrical engineering, renewable energy, and avionics. 🛠️✈️

Awards and Honors:

Dr. Dagal has received several prestigious awards, including the Chad’s Government National Scholarship (2003), Ethiopian Airlines Aviation School International Scholarship (2008), Turkish Government International Scholarship (2015), Young Research Scholarship Award for Eurasia Research (2019), and the Leadership Skills African Civic Engagement Academy (2022). 🏆🌟

Research Focus:

Dr. Dagal’s research interests are centered on optimization algorithms, artificial intelligence, renewable energy systems, power electronics, and aircraft control systems. His doctoral research focused on optimizing photovoltaic battery charging systems using hybrid particle swarm-based algorithms. He has a strong background in developing control mechanisms for sustainable energy systems and dynamic systems in aviation. 🔋🔧🚀

Conclusion:

Dr. Idriss Dagal is an accomplished academic and researcher who combines his expertise in electrical and aerospace engineering with a deep commitment to renewable energy and technology optimization. His interdisciplinary work continues to contribute to advancements in energy systems, aircraft control, and smart technologies. 🌱💻

Publications

Energy transfer from PV panel to Battery via Buck-Boost Converter, International Journal of Technology and Science, Vol. 5, Issue 3, pp. 46-60, 26 November 2019. DOI

Improved salp swarm algorithm based on particle swarm optimization for maximum power point tracking of optimal photovoltaic systems, International Journal of Energy Research, 2022; 1-18. DOI: 10.1002/er.7753. Impact Factor: 4.3, Q1.

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization (PSOSSO) algorithm for battery charging through Simulink, Scientific Reports Journal, 2022; 12:2664. DOI. Impact Factor: 3.8, Q1.

A Novel Hybrid Series Salp Particle Swarm Optimization (SSPSO) for Standalone Battery Charging Applications, Ain Shams Engineering Journal, 2022; 13:10174. DOI. Impact Factor: 6, Q1.

Improved Particle Swarm Optimization based Buck-Boost converter (IPSOBBC) for Photovoltaic System Application, Recent Advances in Science & Engineering (RASE), 2022.

Transformer rail-tapped buck-boost converter design-based feedback controller for battery charging systems, Energy Storage Journal, 2022; e414, DOI. ESCI.

Secure and Optimized Satellite Image Sharing based on Chaotic eπ Map and Racah Moments” Expert Systems with Applications, Volume 236, February 2024, 121247, DOI: 10.1016/j.eswa.2023.121247. Impact Factor: 7.5, Q1.

Hybrid SSA-PSO-based intelligent direct sliding-mode control for extracting maximum photovoltaic output power and regulating the DC-bus voltage, International Journal of Hydrogen Energy, Volume 51, Part C, 2 January 2024, Pages 348-370, DOI. Impact Factor: 8.1, Q1.

An Improved Constant Current Step-based Grey Wolf Optimization Algorithm for Photovoltaic Systems, Journal of Intelligent & Fuzzy Systems, 2024, DOI. Impact Factor: 1.7, Q3.

A Modified Multi-Stepped Constant Current Based on Grey Wolf Algorithm for Photovoltaics Applications, Springer, Electrical Engineering, 2024, DOI. Impact Factor: 1.6, Q3.