Elnaz Yaghoubi is an accomplished Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University, Turkey, where she maintains a perfect GPA of 4.0. Her research focuses on power system analysis, microgrids, and smart grid technologies, with an emphasis on cyber security and model predictive control (MPC). She completed her M.Sc. and B.Sc. degrees in Electrical Engineering with a perfect GPA from Islamic Azad University and Aryan Institute of Science and Technology University, respectively. Elnaz has professional experience in telecommunications, including roles in traffic monitoring and data network design. She is currently a Principal Researcher with the Power Electrical Developing Advanced Research (PEDAR) Group.
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Elnaz Yaghoubi has contributed significantly to her field through a range of scholarly publications. Her work is highly regarded, with several papers accepted or under review in prominent journals such as Engineering Science and Technology and IEEE ACCESS. These publications highlight her expertise in smart grid technologies, microgrid operations, and cyber security, reflecting her impactful contributions to advancing power system engineering.
- Citations: This indicates how many times other researchers have cited Elnaz Yaghoubi’s work. In this case, 73 citations from 71 documents.
- Documents: This shows the number of publications by Elnaz Yaghoubi. She has 8 documents listed.
- h-index: This metric reflects both the productivity and citation impact of her publications. With an h-index of 3, it suggests she has at least 3 papers cited at least 3 times each.
Education
Elnaz Yaghoubi’s educational background is marked by exceptional academic achievements. She is pursuing her Ph.D. in Electronic and Electrical Engineering at Karabuk University, where she has achieved a GPA of 4.0. Her M.Sc. degree in Electrical Engineering from Islamic Azad University and her B.Sc. from Aryan Institute of Science and Technology University also feature perfect GPAs, underscoring her consistent academic excellence. Additionally, she completed an Associate’s degree in Electrical Engineering from the University College of Rouzbahan.
Research Focus
Elnaz Yaghoubi’s research focuses on several key areas within power systems. Her work includes analyzing and enhancing power system stability and management, developing advanced microgrid and smart grid technologies, and integrating renewable energy sources. She also explores Model Predictive Control (MPC) and leverages machine learning techniques, such as artificial neural networks, to improve system performance and security.
Professional Journey
Elnaz Yaghoubi’s professional journey includes significant roles both in academia and industry. As a Principal Researcher at the PEDAR Group, she leads cutting-edge research on power systems and smart grids. Her previous roles include working as an expert in traffic monitoring and data support and in data network design at a major telecommunication company in Iran. These experiences have equipped her with a practical understanding of the challenges in power system management and smart grid implementation.
Honors & Awards
Throughout her academic and professional career, Elnaz Yaghoubi has consistently demonstrated excellence. She has achieved a perfect GPA in all her degrees, reflecting her academic dedication. Her research contributions have been recognized through her involvement in high-impact publications and her role as a Principal Researcher, underscoring her contributions to advancing the field of power system engineering.
Publications Noted & Contributions
Elnaz Yaghoubi has authored several influential publications that contribute to the fields of power systems and smart grids. Her research includes papers on real-time techno-economical operations of microgrids, dynamic reconfiguration for cyber security, and innovative power system risk analysis. Her work, accepted or under review in prestigious journals, demonstrates her role in advancing knowledge and practices in her field.
“Reducing the Vulnerability in Microgrid Power Systems”
- Authors: Ziyodulla Yusupov, Elnaz Yaghoubi, V. Soyibjonov
- Journal: Science and Innovation
- Volume: 2 (A5), Pages: 166-175
- Year: 2023
- Summary: This paper addresses strategies to reduce vulnerabilities in microgrid power systems. It explores various methods for enhancing the resilience and reliability of microgrids, focusing on the integration of advanced technologies and system design improvements.
“A Systematic Review and Meta-Analysis of Artificial Neural Network, Machine Learning, Deep Learning, and Ensemble Learning Approaches in the Field of Geotechnical Engineering”
- Authors: Elnaz Yaghoubi, Elnaz Yaghoubi, Ahmed Khamees, Amir Hossein Vakili
- Journal: Neural Computing and Applications
- Pages: 1-45
- Year: 2024
- Summary: This comprehensive review and meta-analysis examine the application of various learning techniques in geotechnical engineering. The paper evaluates the effectiveness of artificial neural networks, machine learning, deep learning, and ensemble learning approaches in this field.
“Modeling and Control of Decentralized Microgrid Based on Renewable Energy and Electric Vehicle Charging Station”
- Authors: Ziyodulla Yusupov, Nuri Almagrahi, Elnaz Yaghoubi, Elnaz Yaghoubi, Assoc. Prof. Dr. Adib Habbal, Dilshod Kodirov
- Conference: World Conference Intelligent System for Industrial Automation
- Pages: 96-102
- Year: 2022
- Summary: This conference paper discusses the modeling and control mechanisms for decentralized microgrids that incorporate renewable energy sources and EV charging stations. It presents strategies for optimizing microgrid performance and stability.
“Controlling and Tracking the Maximum Active Power Point in a Photovoltaic System Connected to the Grid Using the Fuzzy Neural Controller”
- Authors: Ziyodulla Yusupov, Elnaz Yaghoubi, Elnaz Yaghoubi
- Conference: 2023 14th International Conference on Electrical and Electronics Engineering
- Year: 2023
- Summary: This paper explores a fuzzy neural controller designed to optimize the maximum active power point tracking in photovoltaic systems connected to the grid. The study focuses on improving the efficiency and stability of photovoltaic power systems.
“A Systematic Review and Meta-Analysis of Machine Learning, Deep Learning, and Ensemble Learning Approaches in Predicting EV Charging Behavior”
- Authors: Elnaz Yaghoubi, Elnaz Yaghoubi, Ahmed Khamees, Darioush Razmi, Tianguang Lu
- Journal: Engineering Applications of Artificial Intelligence
- Volume: 135, Article: 108789
- Year: 2024
- Summary: This article provides a systematic review and meta-analysis of various machine learning approaches, including deep learning and ensemble methods, used to predict electric vehicle (EV) charging behavior. The paper aims to synthesize current knowledge and highlight future research opportunities in this area.
Research Timeline
Elnaz Yaghoubi’s research timeline includes her ongoing Ph.D. studies, which began in 2021, focusing on techno-economical management of smart microgrids. She completed her M.Sc. in 2018, where she developed new methodologies for network-on-chip topologies. Her undergraduate studies, culminating in a B.Sc. degree in 2014, provided a strong foundation in electrical engineering principles.
Collaborations and Projects
Elnaz Yaghoubi engages in various collaborations and projects that enhance her research impact. She works with experts in the PEDAR Group and other research networks on projects related to real-time dynamic reconfiguration in smart grids, evaluating power network stability, and developing self-healing frameworks for microgrids. These collaborations highlight her ability to work effectively in interdisciplinary teams to address complex challenges in power systems.
Strengths of the Women Researcher Award
Exceptional Academic Record: Dr. Elnaz Yaghoubi’s consistent achievement of a perfect GPA across all academic levels, including her ongoing Ph.D. at Karabuk University, demonstrates her academic excellence and deep understanding of her field.
High-Impact Research Contributions: Elnaz’s research has made significant contributions to power system analysis, microgrids, smart grids, and cyber security. Her papers are published in high-profile journals and conferences, reflecting her impactful work.
Diverse Research Focus: Her research spans multiple critical areas, including model predictive control (MPC), cyber security, and the integration of renewable energy sources. This diverse focus showcases her versatility and ability to address various complex issues within power systems.
Professional Experience: Elnaz’s experience in telecommunications and her role as a Principal Researcher with the PEDAR Group enhance her practical understanding of power systems and smart grid technologies. This combination of theoretical knowledge and practical experience strengthens her research impact.
Recognition and Awards: Her acknowledgment through the Best Researcher Award highlights her contributions and the high regard in which her work is held. Her multiple publications and citations underline the importance and influence of her research within the academic community.
Areas for Improvement
Expand Citation Impact: While her work is cited, increasing her citation count and h-index would further reflect the broader impact of her research. Engaging in more collaborative projects and high-impact journals could enhance her citation metrics.
Increase Publication Volume: Although her 8 documents are significant, increasing the number of publications, especially in top-tier journals, could further establish her as a leading researcher in her field.
Broaden Research Collaborations: Collaborating with researchers from different disciplines or international institutions could bring new perspectives and expand the scope of her research. This could also lead to more diverse and impactful publications.
Enhance Public Engagement: Increasing visibility through public lectures, media interactions, or industry presentations could help translate her research into practical applications and raise her profile beyond the academic community.
Focus on Emerging Technologies: Exploring emerging technologies and trends within her field, such as quantum computing or advanced artificial intelligence techniques, could keep her research at the cutting edge and open new avenues for impactful work.
Conclusion
Dr. Elnaz Yaghoubi has established herself as a leading researcher in the field of Electronic and Electrical Engineering, with a notable focus on power systems, smart grids, and cyber security. Her impeccable academic record, high-impact research, and professional experience underline her strengths and contributions to the field. To further enhance her recognition and influence, she could focus on expanding her citation impact, increasing publication volume, and engaging in broader collaborations. By addressing these areas, Dr. Yaghoubi can continue to advance her research and maintain her standing as a prominent figure in her field.