Dr. Elaheh Yaghoubi | High Energy Physics | Best Researcher Award
PHD at Karabuk University, Turkey
Professional Profiles
Education
Ph.D. Candidate in Electronic and Electrical Engineering Karabuk University, Turkey (2021-Present) GPA: 4.0/4.0 Thesis: Optimal power control of grid-connected distributed generation in a hierarchical framework based on Model Predictive Control Master of Science in Electrical Engineering Islamic Azad University, Qaemshahr, Mazandaran, Iran (2016-2018) GPA: 4.0/4.0 Thesis: Provide a routing algorithm for the proposed topology for a grid on a large-scale chip to detect an error Bachelor of Science in Electrical Engineering Aryan Institute of Science and Technology University, Iran (2012-2014) GPA: 4.0/4.0 Associate’s Degree in Electrical Engineering University College of Rouzbahan, Iran (2010-2012) GPA: 3.5/4.0
Professional Experience
Principal Researcher PEDAR Group, Remote (2023-Present) Investigation, teaching, and designing in power electrical engineering. Website Designer WebCore Company, Mazandaran, Iran (2019-2021) Designed front-end with HTML, CSS, JavaScript; back-end with PHP, Laravel. Senior Manager Rico Electronics Company, Mazandaran, Iran (2018-2019) Oversaw product quality assurance, ensuring compliance with industry standards, and implemented design modifications. Senior Manager Kati Kabl Tabarestan Factory, Mazandaran, Iran (2015-2018) Managed quality assurance for wire and cable products, proficient in troubleshooting and resolving technical issues.
Research Interests
Power System Analysis, Power System Stability, Power Management Microgrid and Smart Grids Renewable Energies Model Predictive Controllers (MPC) Artificial Neural Networks, Machine Learning, Deep Learning Plasmonic, Nano-Electronic Devices
Awards and Honors
1st Rank among M.Sc. students of Electronics, Islamic Azad University, Qaemshahr, Mazandaran, Iran (2018) 1st Rank among B.Sc. students of Electronics, Aryan Institute of Science and Technology University, Babol, Mazandaran, Iran
Publications
- A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior, Publication date: 2024.
- A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in field of geotechnical engineering, Publication date: 2024.
- Electric vehicles in China, Europe, and the United States: Current trend and market comparison, Publication date: 2024.
- The role of mechanical energy storage systems based on artificial intelligence techniques in future sustainable energy systems, Publication date: 2023.
- Reducing the vulnerability in microgrid power systems, Publication date: 2023.
- Controlling and tracking the maximum active power point in a photovoltaic system connected to the grid using the fuzzy neural controller, Publication date: 2023.
- Modeling and Control of Decentralized Microgrid Based on Renewable Energy and Electric Vehicle Charging Station, Publication date: 2022.
- Tunable band-pass plasmonic filter and wavelength triple-channel demultiplexer based on square nanodisk resonator in MIM waveguide, Publication date: 2022.
- Triple-channel glasses-shape nanoplasmonic demultiplexer based on multi nanodisk resonators in MIM waveguide, Publication date: 2021.