Reem Aljethi | Engineering | Best Researcher Award

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Assist. Prof. Dr. Reem Aljethi | Engineering | Best Researcher Award

Assistant Professor | Imam Mohammad Ibn Saud University | Saudi Arabia

Dr. Reem Abdullah Aljethi is a distinguished Saudi academic and researcher specializing in applied mathematics, with a Doctorate in Applied Mathematics from Universiti Putra Malaysia (UPM), a Master of Science in Applied Mathematics, and a Bachelor of Science (Hons.) in Mathematics from King Saud University. She currently serves as an Associate Professor at Imam Mohammad Ibn Saud Islamic University, where she has also contributed as a lecturer, Vice Dean of the Faculty of Science, and Control Supervisor at Qiyas. Her research expertise encompasses fractional differential equations, stochastic processes, mathematical modeling, and their applications in finance and physics. Dr. Aljethi has authored and co-authored several high-impact Q1 and Q2 publications in reputed journals such as Mathematics, Fractal and Fractional, Chaos, Solitons and Fractals, and Symmetry, contributing significantly to the advancement of fractional calculus and mathematical analysis. With 18 citations across 15 documents, 4 publications, and an h-index of 3, she continues to expand her scholarly impact. Her academic leadership is complemented by her active participation in international conferences, seminars, and faculty development programs, including initiatives promoting women in science and academic leadership training. Dr. Aljethi has been recognized for her contributions through multiple academic and professional honors, reflecting her dedication to excellence in teaching, research, and academic administration. Her ongoing work demonstrates a strong commitment to advancing applied mathematics and fostering interdisciplinary collaborations that address real-world scientific and engineering challenges.

Profile:  Scopus | Orcid 

Featured Publications

Aljethi, R. A., & Kılıçman, A. (2023). Analysis of fractional differential equation and its application to realistic data. Chaos, Solitons & Fractals, 171, 113446.

 

 

 

 

Xinyu Chen | Electrical Engineering | Best Researcher Award

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Ms. Xinyu Chen | Electrical Engineering | Best Researcher Award 

Student | Zhengzhou University of Light Industry | China

Chen Xinyu is a dedicated electrical engineer specializing in R&D testing, electrical systems, and power automation, with academic training covering electrical equipment, power electronics, energy utilization, high voltage technology, relay protection, and power system analysis. She has gained professional experience through internships at Jintai Can Manufacturing, where she worked as a CAD drafting intern, and at Great Wall Motors as an equipment administrator, ensuring safe and stable machinery operations. Her research contributions include developing intelligent systems for monitoring and predicting cable insulation status, conducting in-depth studies on fault diagnosis of power electronic converters using deep learning, and designing advanced methods for partial discharge localization with optimized algorithms, leading to both publications and patents. Her research interests focus on intelligent fault prediction, deep learning applications in converter diagnostics, optimization methods for complex power environments, and predictive maintenance technologies. Recognized with scholarships, technical certifications, and competition awards, she is proficient in tools such as COMSOL, CAD, SolidWorks, MATLAB, Python, and Origin. Combining adaptability, proactive learning, teamwork, and communication skills, she demonstrates resilience and diligence, positioning herself to make valuable contributions to both industry and research while upholding professional excellence.

Profile:  Scopus 

Featured Publications

An, X. (2026). Multi-path propagation homogenization and partial discharge localization method utilizing a multi-mode optimized Squirrel search algorithm. Electric Power Systems Research, 226, 107276.

 

 

 

 

 

Emrah Cetin |Electric Machines | Best Researcher Award

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Assist. Prof. Dr. Emrah Cetin |Electric Machines | Best Researcher Award

Assistant Professor,Tarsus University,Turkey

Assist. Prof. Dr. Emrah Çetin is a faculty member in the Department of Electrical and Electronics Engineering at Tarsus University, Turkey. His research focuses on electric vehicle technologies, motor design, and energy systems. Dr. Çetin has contributed extensively to the development of permanent magnet motors, machine learning applications in autonomous vehicles, and electric drive systems. He has published widely in scientific journals and conferences, showcasing expertise in advanced motor designs and renewable energy technologies

Summary:

Assist. Prof. Dr. Emrah Cetin is a highly skilled and dedicated academic and researcher with a focus on electric machine design, motor drives, and renewable energy systems. His solid academic background, postdoctoral research, and diverse international collaborations position him as a promising candidate for the Best Researcher Award. His research interests align with crucial global challenges, and his academic contributions have the potential to influence both academic and practical advancements in electrical engineering.

 

Professional Profiles:

Scopus

Google Scholar

🎓 Education :

Dr. Emrah Çetin holds a PhD in Electrical and Electronics Engineering from Erciyes University (2012–2018), where he focused on advanced electric machine design and analysis. He also earned his Master’s degree in the same field from Erciyes University (2010–2012), specializing in motor design and power electronics applications. He completed his undergraduate studies in Electrical and Electronics Engineering at Gazi University (2005–2010), establishing a strong foundation in electrical systems.

 

🏢 Experience:

Dr. Çetin is currently an Assistant Professor at Yozgat Bozok University in the Engineering and Architecture Faculty (2018–Present), where he leads research in electric machine design, power electronics, and renewable energy technologies. Previously, he worked as a Postdoctoral Research Associate at the University of Sheffield (2021–2022), focusing on electric machine designs for industrial applications. He also served as a Research Scholar at the University of Wisconsin-Madison’s WEMPEC group (2015–2016), conducting research in electric machine design and power electronics. Earlier, he contributed as a Research Assistant at Erciyes University (2010–2018), participating in several funded projects on electric vehicle motor designs.

🛠️Skills:

Dr. Çetin possesses specialized expertise in electric machine design, particularly in axial flux and permanent magnet machines. He is proficient in developing advanced motor drives for electric vehicles, including the use of brushless DC motors and SiC MOSFETs. His strong knowledge in power electronics and renewable energy technologies, such as wind energy, complements his work on motor drives and electric vehicles. He is fluent in both Turkish and English, which supports his international collaboration and communication in academic research.

 

Research Focus :

Dr. Emrah Çetin’s research focuses on sustainable energy solutions through electric machine design and power electronics. His work is centered on enhancing the efficiency and performance of electric vehicles, particularly through the development of axial flux machines and permanent magnet motors. He also explores renewable energy systems, including wind energy, aiming to create innovative, efficient designs that address the growing global demand for sustainable technologies.

 

🔬Awards:

Dr. Çetin has successfully managed and completed multiple projects, including the “Brushless DC motor drive design for electric vehicles using SiC MOSFETs” (2022) and “Hub Motor Design for Electric Vehicles” (2020). His research contributions are recognized through a h-index of 6, indicating significant academic influence in the field of electrical engineering.

 

Conclusion:

Dr. Cetin demonstrates substantial strengths as an academic and researcher, with a focused and promising research trajectory. However, there is room for growth in terms of increasing his research visibility and broadening his collaborative efforts. With strategic improvements in these areas, Dr. Cetin has the potential to make even more significant contributions to the field of electrical engineering and related industries. Therefore, he is a suitable candidate for the Best Researcher Award, especially considering his ongoing commitment to advancing knowledge in key technological sectors.

 Publications:

  • Cogging torque reduction by utilizing the unequal rotor slot arc method for FSPM Machines
    Author: Çetin, E.
    Journal: Ain Shams Engineering Journal, 2024, 15(11), Article ID: 103008.
    Citations: 0

 

  • The Effects of the Unequal Rotor Slot Arc on Cogging Torque for Flux Switching Permanent Magnet Machines
    Author: Çetin, E.
    Journal: El-Cezeri Journal of Science and Engineering, 2024, 11(1), pp. 73–80.
    Citations: 0

 

  • Rotor pole and stator tooth shaping in FSPM machines for torque performance optimization
    Authors: Çetin, E., Zhu, Z.Q.
    Journal: COMPEL – The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 2024.
    Citations: 0

 

  • Solution of Real-Time Traffic Signs Detection Problem for Autonomous Vehicles by Using YOLOV4 and Haar Cascade Algorithms
    Authors: Ortataş, F.N., Çetin, E.
    Journal: International Journal of Automotive Science and Technology, 2023, 7(2), pp. 125–140.
    Citations: 2

 

  • Torque Effects of the Stator Slot Opening Geometry Error in Production of Axial Flux PM Motors
    Author: Çetin, E.
    Journal: El-Cezeri Journal of Science and Engineering, 2022, 9(3), pp. 1005–1012.
    Citations: 0

 

  • The Performance Comparison of the SiC and Si Mosfets Used in the 3-Phase Brushless DC Motor Drives for Electric Vehicles
    Authors: Sevım, E., Çetin, E.
    Journal: International Journal of Automotive Science and Technology, 2022, 6(4), pp. 331–339.
    Citations: 3

 

  • Optimization of Torque Performance of FSPM Machines by Rotor Pole Shaping using FEA and Genetic Algorithm
    Authors: Çetin, E., Zhu, Z.Q.
    Conference: SMART 2022, 2nd International Conference on Sustainable Mobility Applications, Renewables, and Technology, 2022.
    Citations: 4

 

  • Lane Tracking with Deep Learning: Mask RCNN and Faster RCNN
    Authors: Ortatas, F.N., Çetin, E.
    Conference: ASYU 2022, Innovations in Intelligent Systems and Applications Conference, 2022.
    Citations: 5

 

  • Comparative Study of Yokeless Dual-rotor and External-rotor Radial-Flux Fractional-Slot PM Machines
    Authors: Ran, Z.T., Zhu, Z.Q., Wei, F.R., Çetin, E.
    Conference: ICEM 2022, International Conference on Electrical Machines, 2022, pp. 1913–1919.
    Citations: 3

 

  • Traffic sign recognition and the application of simulation using machine learning in electric and autonomous vehicles
    Authors: Ortataş, F.N., Çetin, E.
    Journal: El-Cezeri Journal of Science and Engineering, 2021, 8(3), pp. 1081–1092.
    Citations: 4