Elnaz Yaghoubi | Power System Analysis | Best Researcher Award

Dr. Elnaz Yaghoubi, karabuk university, Turkey.

Elnaz Yaghoubi is a dedicated Ph.D. candidate in Electronic and Electrical Engineering at Karabuk University, Turkey, boasting a stellar GPA of 4.0. Her research specializes in power system analysis, microgrids, and renewable energy. Elnaz holds an M.Sc. in Electrical Engineering from Islamic Azad University, also achieving a perfect GPA. She has worked as an engineering expert at Iran’s Telecommunication Company and is an active member of the PEDAR research group, contributing to innovative projects in smart grid technology. With a passion for advancing energy solutions, Elnaz is a rising star in her field.

Professional Profile:

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Education and Experience:

Ph.D. in Electronic and Electrical Engineering
Karabuk University, Turkey (2021-Present)
Thesis: Techno-economical reliable energy management of smart microgrids
GPA: 4.0
M.Sc. in Electrical Engineering
Islamic Azad University, Qaemshahr, Iran (2016-2018)
Thesis: New topology based on clustering for network on chip
GPA: 4.0
B.Sc. in Electrical Engineering
Aryan Institute of Science and Technology, Iran (2012-2014)
GPA: 4.0
Associate’s Degree in Electrical Engineering
University College of Rouzbahan, Iran (2010-2012)
GPA: 4.0
Principle Researcher
PEDAR Group (2023-Present)
Expert in Traffic Monitoring and Data Support
Telecommunication Company, Iran (2017-2021)
Data Network Design
Telecommunication Company, Iran (2015-2017)

Suitability for Best Researcher Award:

Dr. Elnaz Yaghoubi is an exemplary candidate for the Best Researcher Award in the field of Electronic and Electrical Engineering due to her academic excellence, impactful research contributions, and professional experience.

Professional Development:

Elnaz Yaghoubi is continually enhancing her skills and expertise through various professional development avenues. She possesses strong programming skills in MATLAB and C++ and is currently expanding her knowledge in Python and Linux Essentials. With experience in machine learning and deep learning techniques, she actively engages in research and development within the PEDAR research group. Her proficiency in software tools like AutoCAD and Proteus, alongside certifications in network and security fundamentals, underlines her commitment to staying at the forefront of technological advancements in power systems.

Research Focus:

Elnaz Yaghoubi’s research primarily revolves around power system analysis, focusing on optimizing power management in microgrids and smart grids. She explores renewable energy solutions and the integration of distributed generation methods to enhance energy efficiency. Additionally, Elnaz delves into model predictive control (MPC) for advanced power control strategies, emphasizing cyber security in energy systems. Her work with artificial neural networks and machine learning further supports innovative solutions in the field. Elnaz’s commitment to addressing contemporary energy challenges makes her a pivotal figure in advancing smart energy technologies.

Awards and Honors:

Perfect GPA Award (Karabuk University)
Outstanding Research Contribution Award (Islamic Azad University)
Best Paper Award (Conference on Renewable Energy Solutions)
Excellence in Engineering Award (Telecommunication Company, Iran)
Leadership in Research Award (PEDAR Group)

Publication top Notes:

State-of-the-art review on energy and load forecasting in microgrids using artificial neural networks, machine learning, and deep learning techniques
Cited by: 85 | Year: 2023
The role of mechanical energy storage systems based on artificial intelligence techniques in future sustainable energy systems
Cited by: 15 | Year: 2023
Triple-channel glasses-shape nanoplasmonic demultiplexer based on multi nanodisk resonators in MIM waveguide
Cited by: 12 | Year: 2021
Reducing the vulnerability in microgrid power systems
Cited by: 11 | Year: 2023
Electric vehicles in China, Europe, and the United States: Current trend and market comparison
Cited by: 10 | Year: 2024
Tunable band-pass plasmonic filter and wavelength triple-channel demultiplexer based on square nanodisk resonator in MIM waveguide
Cited by: 10 | Year: 2022
A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior
Cited by: 9 | Year: 2024

Prof. Niranjan Nayak, Siksha ‘O’ Anusandhan, Bhubaneswar, INDIA

Prof. (Dr.) Niranjan Nayak is a distinguished academic and researcher with extensive expertise in Electrical and Electronics Engineering. He earned his B.Tech in Engineering from the Institution of Engineers, Kolkata, in 1992, followed by a Master’s degree from University College of Engineering (now Vir Surendra Sai University of Technology) in 2003, and a Ph.D. from Siksha ‘O’ Anusandhan University in 2015. Currently, Dr. Nayak serves as a Professor at Siksha ‘O’ Anusandhan University, India, where his research interests include energy management, energy storage and conversion, microgrid control, renewable energy, optimal control, electric vehicles (EV), evolutionary computing, and machine learning. With over 100 publications in renowned journals and international conferences, Dr. Nayak has made significant contributions to his field. He has also edited three major conference proceedings and chaired international conferences, including AECSS-2019 and APSIT-2021 and 2023. As a dedicated member of IEEE, IE, IET, and ISTE, he actively reviews for various international journals under prestigious publishers such as IEEE and Elsevier. Dr. Nayak’s work continues to advance innovation in electrical and electronics engineering.

Summary of Suitability for Best Researcher Award

Prof. (Dr.) Niranjan Nayak is a highly accomplished academic and researcher, making him a strong contender for the Best Researcher Award. His extensive academic journey, starting with his B.Tech from the Institution of Engineers, Kolkata, followed by a Master’s degree from University College of Engineering, and culminating in a Ph.D. from Siksha ‘O’ Anusandhan (Deemed to be University), reflects a solid foundation in Electrical and Electronics Engineering.

Education:

B.Tech in Engineering from the Institution of Engineers, Kolkata, India, in 1992.
Master’s degree from University College of Engineering (UCE), currently known as Vir Surendra Sai University of Technology (VSUT), in 2003.
Ph.D. degree from Siksha ‘O’ Anusandhan deemed to be university, India, in 2015.

Work Experience:

Professor in the Department of Electrical & Electronics Engineering, Faculty of Engineering, Siksha ‘O’ Anusandhan deemed to be university, India.
- Has authored and co-authored around 100 journals and international conference papers.
- Current research interests include energy management, energy storage & conversion, microgrid control, renewable energy, optimal control, electric vehicles (EV), evolutionary computing, and machine learning.
- Edited three conference proceedings: AECSS-2019, APSIT-2021, and APSIT-2023.
- Served as the General Chair of the 1st International Conference on Advances in Electrical Control and Signal System (AECSS-2019), and also for Advances in Electrical Power, Signal & Information Technology (APSIT-2021 and APSIT-2023).
- Reviewer for several international journals under IEEE, Elsevier, and other publishers.
- Member of IEEE, IE, IET, and ISTE.

Publication top Notes:

A new representation learning based maximum power operation towards improved energy management integration with DG controllers for photovoltaic generators using online deep exponentially expanded RVFLN algorithm