Merve Öztekin | Engineering | Innovative Research Award

Innovative Research Award

Merve Öztekin
Karadeniz Technical University, Turkey
Merve Öztekin
Affiliation Karadeniz Technical University
Country Turkey
Scopus ID 57848993700
Documents 2
Citations 3
h-index 1
Subject Area Engineering
Event Global Innovation Technologist Awards
ORCID 0009-0007-0470-6229

The Innovative Research Award recognizes researchers whose scholarly activities contribute to technological advancement through high-quality engineering research and measurable scientific outputs. Merve Öztekin of Karadeniz Technical University has developed research focused on transformer differential protection, electrical machines, intelligent control systems, and electric vehicle drive technologies. Recent publications demonstrate continued engagement with modern power engineering challenges while emphasizing analytical methods and practical applications in electrical power systems.[1]

Abstract

Merve Öztekin’s research addresses transformer protection algorithms, wavelet-transform applications, nonlinear motor control, and energy-efficient electric vehicle drive systems. The published work combines theoretical modelling with engineering implementation, contributing to the reliability and efficiency of electrical power equipment. The research portfolio reflects interdisciplinary integration between protection engineering, control theory, and intelligent electrical systems.[2]

Keywords

Transformer Differential Protection, Wavelet Transform, Electric Vehicles, Interior Permanent Magnet Synchronous Motor, Engineering, Power Systems, Electrical Protection, Intelligent Control.

Introduction

Modern electrical engineering increasingly requires dependable protection techniques and efficient motor control strategies to improve system stability and sustainability. Research undertaken by Merve Öztekin contributes to these objectives through investigations into transformer fault detection and optimized electrical drive technologies. Publications appearing in international journals and conference proceedings demonstrate ongoing participation in engineering research.[3]

Research Profile

According to the supplied research profile, the author has published studies involving transformer differential protection algorithms, electric vehicle drive optimization, nonlinear control methods, and power electronics. The available bibliometric indicators include a Scopus Author ID of 57848993700 with documented scholarly output, citations, and an h-index reflecting the current stage of academic development.[1]

Research Contributions

  • Development of low-level inter-turn fault detection algorithms for transformer differential protection.
  • Application of wavelet transform techniques for reliable transformer protection.
  • Research on nonlinear optimal control for interior permanent magnet synchronous motors.
  • Studies supporting energy-efficient electric vehicle drive systems.

Publications

  • Low-Level Inter-Turn Fault Detection Algorithm for Transformer Differential Protection (Applied Sciences, 2026).
  • Transformer Differential Protection with Wavelet Transform and Difference Function (Engineering Science and Technology, 2025).
  • Energy Efficient and Transients Optimal IPMSM Drive for Electric Vehicles (SPEEDAM, 2022).
  • Nonlinear Optimal Control for Interior Permanent Magnet Synchronous Motor Drives (ECC, 2022).
  • Wavelet Transform Based Differential Protection Algorithm for Power Transformer (ELECO, 2016).

Research Impact

The available publication record illustrates sustained interest in power system protection and electric drive optimization. Citation metrics indicate emerging scholarly recognition, while recent journal publications suggest continued research productivity. The work contributes to engineering literature by addressing practical reliability and efficiency challenges in electrical infrastructure.[4]

Award Suitability

Based on the documented publications, engineering specialization, and recent peer-reviewed contributions, Merve Öztekin demonstrates characteristics consistent with consideration for the Global Innovation Technologist Awards. The research portfolio emphasizes innovation in electrical engineering through analytical modelling, transformer protection, and sustainable transportation technologies while maintaining publication activity in recognized scientific venues.[5]

Conclusion

The academic profile presented here reflects an engineering researcher contributing to electrical power systems, intelligent protection methods, and advanced motor control. Through conference papers and peer-reviewed journal articles, the research demonstrates progressive development and continuing engagement with contemporary engineering challenges. The documented achievements provide an appropriate scholarly basis for recognition within an international innovation-focused award framework.

References

  1. Elsevier. (n.d.). Scopus author details: Merve Öztekin, Author ID 57848993700.
    https://www.scopus.com/authid/detail.uri?authorId=57848993700
  2. Öztekin, M. (2026). Low-Level Inter-Turn Fault Detection Algorithm for Transformer Differential Protection.
    https://doi.org/10.3390/app16147073
  3. Öztekin, M. (2025). Transformer Differential Protection with Wavelet Transform and Difference Function.
    https://doi.org/10.1016/j.jestch.2025.102144
  4. IEEE. (2022). Energy Efficient and Transients Optimal IPMSM Drive for Electric Vehicles.
    https://doi.org/10.1109/SPEEDAM53979.2022.9842114
  5. European Control Conference. (2022). Nonlinear Optimal Control for Interior Permanent Magnet Synchronous Motor Drives.
    https://doi.org/10.23919/ECC55457.2022.9838314

Zhiqi Wu | Engineering | Best Researcher Award

Ms. Zhiqi Wu | Engineering | Best Researcher Award

Student at Anhui University of Science and Technology | China

Zhiqi Wu is a Master’s student in Electrical Engineering at Anhui University of Science and Technology, specializing in computer vision applications for intelligent coal gangue detection. His research emphasizes developing lightweight, high-performance models that improve automation and efficiency in mining operations. Zhiqi proposed a novel model integrating multispectral imaging with knowledge distillation, achieving a precision increase of up to 6% while reducing model size by 21.8%, enabling deployment on mobile and edge devices for real-time sorting. This approach advances intelligent coal industry practices by combining computational efficiency with practical industrial applicability. Zhiqi’s work exemplifies the translation of advanced AI techniques into actionable solutions for industrial automation, with a focus on scalability, accuracy, and sustainability. His contributions are recognized in the research community, with 1 citation for his published work, highlighting its impact and relevance. To date, he has contributed to 4 documents in his research portfolio, reflecting his engagement in ongoing innovation and knowledge dissemination. While his h-index currently stands at 1, it represents a promising start in a career dedicated to applied AI in mining technologies. Zhiqi continues to explore methods for optimizing computer vision systems in industrial contexts, advancing automation, operational safety, and resource efficiency. His work bridges theoretical research and practical deployment, positioning him as an emerging researcher making measurable contributions to intelligent mining technologies.

Profile: Scopus

Featured Publications

Yan, P. (2025). Transformer fault diagnosis based on LIF technology and COA-GRU algorithm. Engineering Research Express, 7(2), 25409.