Rahim Zahedi | Energy | Best Researcher Award

Best Researcher Award

Rahim Zahedi
University of Tehran

Rahim Zahedi
Affiliation University of Tehran
Country Iran
Google Scholar ID uMoggwwAAAAJ
Documents 168
Citations 5,188
h-index 38
Subject Area Energy
Award Best Researcher Award
Event International Invention Awards
ORCID 0000-0001-6837-8729

Rahim Zahedi is a researcher affiliated with the University of Tehran, Iran, whose identified subject area is energy. His academic profile reports 168 documents, 5,188 citations, and an h-index of 38. These indicators provide quantitative context for assessing research productivity and scholarly visibility. His profile is presented in connection with the Best Researcher Award at the International Invention Awards, recognizing documented academic activity and research contributions.
[1]

Abstract

Rahim Zahedi is a researcher affiliated with the University of Tehran whose identified subject area is energy. His supplied academic profile reports 168 documents, 5,188 citations, and an h-index of 38, indicating sustained scholarly activity and measurable citation visibility. This article presents his research profile in relation to the Best Researcher Award associated with the International Invention Awards. The assessment considers publication activity, research contributions, scholarly impact, and academic suitability for recognition. Quantitative indicators are used as supporting evidence rather than definitive measures of research quality. A comprehensive evaluation should also consider originality, methodological rigor, relevance, authorship, and documented contributions to energy research and innovation.

Keywords

Rahim Zahedi; University of Tehran; Energy Research; Researcher; Best Researcher Award; International Invention Awards; Research Productivity; Scholarly Impact; Citation Analysis; h-index.

Introduction

Academic recognition generally considers research productivity, scholarly quality, disciplinary contribution, and influence within the research community. Rahim Zahedi is identified with the University of Tehran and the energy research field. His reported publication and citation indicators provide a quantitative foundation for describing his academic activity. However, bibliometric measures are most appropriately interpreted alongside qualitative evidence concerning originality, research methodology, relevance, and contribution to knowledge. [1] [2]

Research Profile

Rahim Zahedi’s supplied academic information identifies the University of Tehran as his institutional affiliation and Iran as his country. His research subject area is energy, with a reported record of 168 documents, 5,188 citations, and an h-index of 38. These figures describe a substantial level of documented scholarly activity and provide measurable context for reviewing his academic profile. [1]

Research Contributions

The research profile of Rahim Zahedi is situated within the broad field of energy research. Academic contributions in this area may address scientific analysis, energy systems, technological development, efficiency, sustainability, or related applications. A detailed evaluation of specific contributions requires examination of the underlying publications and research outputs, including their methodology, originality, relevance, and influence within the scientific literature.

Publications

The supplied profile reports 168 documents associated with Rahim Zahedi. This figure indicates sustained scholarly publication activity. Publication quantity alone does not determine academic quality, and appropriate evaluation should also consider the significance of individual studies, authorship contribution, research methodology, publication venues, originality, and relevance. Persistent researcher identifiers such as ORCID can assist in accurately associating scholarly outputs with individual researchers. [3]

Research Impact

The reported citation count of 5,188 and h-index of 38 provide quantitative measures of scholarly visibility. The h-index is designed to combine publication productivity and citation impact into a single indicator, although its interpretation differs between disciplines and career stages. [2] Accordingly, these values should be treated as contextual indicators and considered together with qualitative evidence concerning the researcher’s substantive academic contributions.

Award Suitability

The supplied academic profile provides several measurable indicators relevant to consideration for the Best Researcher Award. Rahim Zahedi’s affiliation with the University of Tehran, specialization in energy, reported publication record, citation count, and h-index collectively establish a documented scholarly profile. Final award evaluation should additionally consider verified research outputs, originality, scientific quality, contribution to the field, and the formal assessment criteria applied by the International Invention Awards.

Conclusion

Rahim Zahedi, affiliated with the University of Tehran, has a supplied academic profile reflecting sustained research activity in the energy field. The reported record of 168 documents, 5,188 citations, and an h-index of 38 provides quantitative context for evaluating his scholarly visibility. These indicators can support consideration for the Best Researcher Award, while a complete assessment should incorporate qualitative evidence concerning research originality, rigor, relevance, and contribution to the scientific community.

References

  1. Google Scholar. (n.d.). Rahim Zahedi, Author ID uMoggwwAAAAJ. Google Scholar author profile.
    https://scholar.google.com/citations?hl=en&user=uMoggwwAAAAJ
  2. Journal article. (2025).Technical and economic analysis of hydrogen production from pre combustion carbon capture by Rectisol process in combined cycle power plant..
    https://doi.org/10.1016/j.enconman.2025.120290
  3. ORCID. (n.d.). Rahim Zahedi, ORCID record 0000-0001-6837-8729.
    https://orcid.org/0000-0001-6837-8729
  4. Journal article. (2026).Enhancing power, water and biofuel multigeneration system through developed biomass-driven hybrid process with energy, exergy, economic and environmental (4E) analysis.
    https://doi.org/10.1016/j.renene.2025.124131
  5. International Invention Awards. (2026.). International Invention Awards official website.
    https://inventionawards.org/

 

Oussama Khouili | Energy | Excellence in Research Award

Mr. Oussama Khouili | Energy | Excellence in Research Award

National School of Scientific Applications, Morocco

Mr. Oussama Khouili is a PhD student at ENSA El Jadida, Chouaib Doukkali University, specializing in the integration of Artificial Intelligence and Renewable Energy with a focus on solar irradiance forecasting and photovoltaic system optimization. His research develops advanced Machine Learning and Deep Learning models, including ShuffleNet, CNNs, physics-guided networks, PCA-based transformations, FFT techniques, and metaheuristic optimization algorithms such as Particle Swarm Optimization. He has completed and is leading multiple projects on solar prediction accuracy, feature selection methods, smart grid technologies, and AI-driven renewable energy solutions. He has authored peer-reviewed articles in prestigious SCI and Scopus-indexed journals including Energy Strategy Reviews, International Journal of Energy Research, and IEEE Power Electronics Magazine, with 29 citations and an h-index of 2. He has also published four ISBN-indexed book chapters on AI applications in renewable energy and environmental management systems such as ISO 14001. Recognized with a Research Excellence Award, he actively contributes as an independent reviewer and collaborates internationally to bridge advanced computational intelligence with sustainable energy solutions addressing global climate challenges.

Citation Metrics (Scopus)

25
20
15
10
5
0

Citations
23

Documents
9

h-index
2

Citations

Documents

h-index

View Scopus Profile

Featured Publications

 

Prof. Dr. Chao Lyu | Energy | Best Researcher Award

Prof. Dr. Chao Lyu | Energy | Best Researcher Award

Harbin Institute of Technology, China.

Prof. Chao Lyu is a distinguished scholar and researcher in electrical engineering, specializing in battery modeling, battery health management, and microgrid optimization. He is a Professor and Doctoral Supervisor at the Harbin Institute of Technology and a Senior Member of IEEE. With a strong academic background and over 50 research publications in international journals and conferences, Prof. Lyu has made significant contributions to the field of energy storage systems and lithium-ion battery technology. His expertise extends to fault diagnosis, performance evaluation, and optimization control methods for energy storage batteries, shaping advancements in sustainable energy solutions.

Profile

Scopus

Google Scholar

πŸŽ“ Education

Prof. Chao Lyu holds a strong academic foundation in electrical engineering. He earned his B.Eng. in Electrical Engineering from Northeast Electric Power University, Jilin, China, in 2001, followed by an M.Sc. in Electrical Engineering from the same institution in 2004. His pursuit of advanced research led him to complete a Ph.D. in Electrical Engineering at Harbin Institute of Technology, China, in 2007. His academic journey has equipped him with extensive expertise in battery modeling, energy storage systems, and microgrid optimization, laying the groundwork for his impactful research and contributions to the field.

πŸ’Ό Professional Experience

Prof. Chao Lyu is a Professor and Doctoral Supervisor at Harbin Institute of Technology, where he leads research in battery modeling, energy storage systems, and microgrid optimization. As a Senior Member of IEEE, he actively contributes to advancements in electrical engineering and battery technology. Beyond academia, he serves as a researcher and consultant, collaborating with State Grid Corporation of China and Guangdong Power Grid Co., Ltd on industry-driven projects focused on battery fault diagnosis, performance evaluation, and optimization control. His work bridges the gap between research and real-world applications, driving innovation in sustainable energy solutions.

πŸ”¬ Research Interests

Battery Modeling & Testing πŸ”‹

Battery Health Management & Fault Diagnosis ⚑

Microgrid Optimization with Energy Storage 🏭

Lithium-ion Battery Performance & Safety πŸ”

Artificial Intelligence for Battery Management πŸ€–

πŸ† Awards & Recognitions

Senior Member, IEEE

Recognized Expert in Battery Technology & Microgrid Systems

πŸ“š Selected Publications

Early Internal Short Circuit Diagnosis for Lithium-Ion Battery Packs Based on Dynamic Time Warping of Incremental Capacity – Batteries, 10(11), 378

Concurrent Multi-Fault Diagnosis of Lithium-Ion Battery Packs Using Random Convolution Kernel Transformation and Gaussian Process Classifier – Energy, 306, 132467 (3 citations)

Model-Free Detection and Quantitative Assessment of Micro Short Circuits in Lithium-Ion Battery Packs Based on Incremental Capacity and Unsupervised Clustering – International Journal of Electrochemical Science, 19(10), 100794 (1 citation)

Digital Twin Modeling Method for Lithium-Ion Batteries Based on Data-Mechanism Fusion Driving – Green Energy and Intelligent Transportation, 3(5), 100162 (3 citations)

Optimization of Lithium-Ion Battery Charging Strategies From a Thermal Safety Perspective – IEEE Transactions on Transportation Electrification, 10(2), pp. 2727–2739

 

 

 

Mr. Xinyang Yao | Energy | Best Researcher Award

Mr. Xinyang Yao | Energy | Best Researcher Award

Xinjiang University, China.

Xinyang Yao is a dedicated postgraduate researcher specializing in underground coal gasification at the Xinjiang Key Laboratory for Geodynamic Processes and Metallogenic Prognosis of the Central Asian Orogenic Belt. With a strong theoretical foundation and hands-on experimental skills, Xinyang's research focuses on technological innovation in unconventional resource development. His work contributes to the advancement of efficient and safe gasification technologies, improving practical applications in the field.

Profile

Orcid

Education πŸŽ“

Postgraduate degree in Underground Coal Gasification, specializing in geodynamic processes and metallogenic prognosis.

Experience πŸ”¬

Joint research with PetroChina Xinjiang Oilfield Company, where Xinyang was responsible for numerical simulation in underground coal gasification. He has also actively contributed to research projects that optimize gasification schemes, focusing on induced fractures and stress concentration in practical UCG projects.

Research Interests πŸ’‘

Underground Coal Gasification (UCG)

Unconventional Resource Development

Geodynamic Processes

Numerical Simulation for UCG Applications

Publication πŸ“š

Numerical simulations of fracture propagation in overlying strata for deep underground coal gasification using controlled retraction injection point technology

Journal: Energy

Published Year: 2025

Contributors: Xinyang Yao, Xin Li, Bo Wei, Jijun Tian, Shuguang Yang, Yiwen Ju

 

 

Assoc. Prof. Dr. Ruiming Fang | Photocatalysis | Best Researcher Award

Assoc. Prof. Dr. Ruiming Fang | Photocatalysis | Best Researcher Award

Anhui University of Technology, China.

Fang Ruiming is an Associate Professor at the School of Energy and Environmental Engineering, Anhui University of Technology. Currently pursuing a Ph.D. jointly trained by Chongqing University and Nanyang Technological University, Singapore, his work centers on CO2 valorization and photocatalytic processes for hydrogen production. With over 400 citations across 20 publications in prestigious journals, including Journal of Materials Chemistry A and Energy and Fuel, he has garnered recognition through awards like the National Scholarship for Graduate Students in High-level University Construction and the Outstanding Graduate Student Honor from Chongqing University.

Profile

Scopus

Google Scholar

Education πŸŽ“

Dr. Ruiming Fang is currently pursuing his Ph.D. as a joint candidate between Chongqing University, China, and Nanyang Technological University, Singapore, specializing in energy and environmental engineering. This collaborative training program enables him to merge cutting-edge research approaches from two prestigious institutions. Prior to his Ph.D., he earned both his Master’s and Bachelor’s degrees in Energy and Environmental Engineering, laying a strong foundation in sustainable energy technologies, environmental processes, and advanced material applications. His academic journey reflects a commitment to tackling global energy and environmental challenges through innovative research and interdisciplinary collaboration.

Experience πŸ’Ό

Dr. Ruiming Fang serves as an Associate Professor at the School of Energy and Environmental Engineering, Anhui University of Technology, where he contributes to advancing sustainable energy solutions. As a Guest Editor for the Special Issue "Impacts of Combustion and Thermo-Chemistry", he actively collaborates with the global research community to address pressing issues in energy transformation and carbon reduction technologies.

With a focus on CO2 valorization, photocatalysis, and hydrogen production mechanisms, Dr. Fang's research explores innovative pathways to sustainable energy generation. His work on catalytic systems and reaction mechanisms has provided groundbreaking insights into renewable energy processes, enhancing both academic and industrial applications.

Research Interests πŸ”¬

CO2 Valorization

Innovative solutions to convert CO2 into valuable products

Photocatalysis

Mechanisms and material development for hydrogen production

Sustainable Energy Systems

Advanced catalytic systems such as borane-ammonia complexes

Awards πŸ†

National Scholarship for Graduate Students in High-level University Construction
Outstanding Graduate Student Honor, Chongqing University

Selected Publications πŸ“š

"Constructing and strengthening the 'Electron Bridge' of BMO/CPP to enhance photothermal synergistic catalytic CO2 reduction"
Wu, X., Guo, M., Wang, Z., ... He, J., Yang, Z.
Separation and Purification Technology, 2024, 345, 127330.
Cited by: 2 articles.

"Double defects cooperatively mediated BiOClBr-OV for efficient round-the-clock photocatalytic CO2 reduction"
Fang, R., Yang, Z., Wang, Z., ... Ran, J., Godin, R.
Fuel, 2024, 367, 131514.
Cited by: 5 articles.

"g-C3N4@CPP/BiOClBr-OV biomimetic fractal heterojunction synergistically enhance carrier dynamics for boosted CO2 photoreduction activity"
Fang, R., Yang, Z., Guo, M., ... Ran, J., Xue, C.
Applied Surface Science, 2024, 656, 159712.
Cited by: 3 articles.

"Dioxygen atom co-doping g-C3N4 for boosted photoreduction activity of CO2 and mechanistic investigation"
Jiang, Z., Guo, M., Yang, Z., ... Wang, Z., Ran, J.
Journal of Materials Chemistry A, 2024, 12(19), pp. 11591–11601.
Cited by: 3 articles.

"Synergistic mediation of dual donor levels in CNS/BOCB-OV heterojunctions for enhanced photocatalytic CO2 reduction"
Fang, R., Yang, Z., Sun, J., ... Wang, Z., Xue, C.
Journal of Materials Chemistry A, 2024, 12(6), pp. 3398–3410.
Cited by: 7 articles.

 

 

Dr. Zhonghua Liu | Petroleum engineering | Best Researcher Award

Dr. Zhonghua Liu | Petroleum engineering | Best Researcher Award

Chongqing university of science and technology, China

Dr. Zhonghua Liu is an Associate Professor at the School of Petroleum and Natural Gas Engineering at Chongqing University of Science & Technology in China. With over a decade of experience in petroleum engineering, his work has primarily focused on shale gas development and reservoir characterization. Dr. Liu has also gained valuable international experience as a visiting scholar at Missouri University of Science and Technology. He has made substantial contributions to the understanding of gas recovery and multiphase flow in porous media, positioning him as a notable researcher in the field.

Profile

Orcid

Google Scholar

EducationπŸŽ“

Dr. Liu earned his Ph.D. in Oil & Gas Field Development Engineering from China University of Petroleum (East China) in 2022. Prior to this, he completed his M.S. in Oil & Gas Field Development Engineering at Chengdu University of Technology in 2012 and his B.S. in Petroleum and Natural Gas Engineering at Yangtze University in 2005. His academic journey laid a solid foundation for his research in petroleum and natural gas engineering, particularly in shale gas reservoir management.

ExperienceπŸ§‘β€πŸ”¬

Dr. Liu has a diverse professional background that spans academia and industry. He currently serves as an Associate Professor at Chongqing University of Science & Technology, a role he assumed in December 2022. Prior to this, he held a lecturer position at the same institution from 2012 to 2022 and served as a visiting scholar at Missouri University of Science and Technology in 2021. His industry experience includes his early role as an oil testing technician at Jilin Oilfield Company, where he developed practical insights into oil testing and reservoir management.

Research InterestsπŸ”¬

Shale Gas Development

Dr. Liu’s primary research focuses on advancing shale gas development, where he investigates methods to optimize extraction processes and enhance gas yield. His work in this area contributes to increasing the efficiency and sustainability of shale gas production, addressing both technical and environmental challenges.

Core Pore Structure Characterization

Dr. Liu conducts detailed studies on the pore structure of shale formations to better understand how gas is stored and flows within these reservoirs. By characterizing core pore structures, he aims to refine models that predict gas behavior in unconventional reservoirs, which is crucial for effective extraction and management.

Geological Carbon Sequestration

In addition to gas extraction, Dr. Liu is engaged in research on geological carbon sequestration. His studies in this area are focused on the potential for storing COβ‚‚ in depleted or active shale gas reservoirs, a process that can mitigate carbon emissions while enhancing gas recovery. This dual-purpose approach aligns with global efforts to reduce greenhouse gas emissions.

Enhancing Gas Recovery Methods

Dr. Liu is actively working on developing innovative methods for enhancing gas recovery from shale reservoirs. His research explores advanced techniques that improve the efficiency of gas extraction, including hydraulic fracturing optimization and multiphase flow analysis. These efforts are aimed at maximizing resource utilization and minimizing operational costs.

Multiphase Flow in Porous Media

A significant part of Dr. Liu’s research is dedicated to understanding multiphase flow within porous media. By studying how gas, water, and other fluids interact within shale formations, he seeks to create predictive models that improve our understanding of flow dynamics in complex geological structures. This research is essential for enhancing both extraction and storage strategies in shale gas reservoirs.

Honors and AwardsπŸ†

Dr. Liu has been recognized for his contributions to the petroleum industry with several awards. Notably, he received the Second Prize of Scientific and Technological Progress from the China Petroleum and Chemical Automation Application Association in 2022 for his work on fractured horizontal wells in deep offshore shale gas reservoirs. This award highlights his innovative approach to enhancing the efficiency and effectiveness of gas extraction processes.

Publications Top NotesπŸ“š

Liu, Z., Ding, Z., Yang, H., et al. "Lab-Scale Investigation of Slickwater Impact on Methane Desorption on Longmaxi Gas Shale." Chemical Engineering and Technology, 2023. Link

Liu, Z., Xie, Y., Yang, H., et al. "Interaction between slick water and gas shale and its impact on methane desorption." Petroleum Science and Technology, 2023. Link

Liu, Z., Wang, J., Bai, B.J., et al. "Impact of clay stabilizer on the methane desorption kinetics of Longmaxi Shale." Petroleum Science, 2022. Link

Liu, Z., Bai, B.J., Wang, Y.L. "Experimental Study of Defoamer Effect on Methane Desorption." Springer Series in Geomechanics and Geoengineering, 2022. Link

 

 

 

 

 

 

 

Elaheh Yaghoubi | Energy | Best Researcher Award

Dr. Elaheh Yaghoubi | Energy | Best Researcher Award

Electrical engineering of Karabuk university, Turkey

Dr. Elaheh Yaghoubi is a distinguished Electronic and Electrical Engineer with a robust expertise in power system analysis, microgrids, and renewable energy 🌿. Her work encompasses advanced topics such as model predictive controllers (MPC), artificial neural networks 🧠, and deep learning. Dr. Yaghoubi has managed quality control projects for sockets, plugs, wires, and cables in Iran, ensuring top-notch standards πŸ”Œ. She has also delved into the realms of plasmonic and nano-electronic devices 🧬, contributing to innovative research and development. Based in Karabuk, Turkey, Dr. Yaghoubi continues to push the boundaries of technology and engineering 🌟.

Professional Profile:

EducationπŸŽ“

Dr. Elaheh Yaghoubi boasts an impressive academic background πŸ“š. She has earned her Ph.D. in Electronic and Electrical Engineering, specializing in power systems and renewable energy technologies ⚑. Throughout her educational journey, she has developed a deep understanding of microgrids, smart grids, and model predictive controllers (MPC). Dr. Yaghoubi has also enhanced her expertise through various training programs, including Internet of Things (IoT) and Python programming πŸ–₯️, solidifying her knowledge in cutting-edge technologies and their applications. Her continuous pursuit of learning has equipped her with the skills necessary to excel in both research and practical engineering environments πŸ§ πŸŽ“.

 

Professional Experience πŸ“š

 

Dr. Elaheh Yaghoubi has garnered extensive professional experience in the field of electronic and electrical engineering πŸ’Ό. She has played a pivotal role in the simulation and programming of microgrids and power systems at PEDAR Group, where she worked remotely to ensure high standards of quality and efficiency πŸ”Œ. Her expertise extends to quality control, having managed the quality control of sockets, plugs, electronic shields, wires, and cables at Standard Organization in both Tehran and Semnan, Iran πŸ› οΈ. Additionally, Dr. Yaghoubi has completed specialized training in ICDL, IoT, Python, Android app development with Kotlin, and PHP, further enhancing her technical capabilities and versatility in the engineering domain πŸŒπŸ“±.

Research Interest πŸ”

Dr. Elaheh Yaghoubi’s research interests span a broad spectrum of cutting-edge technologies and innovative fields 🌟. She delves into power system analysis, power system stability, and power management, focusing on the intricacies of microgrids and smart grids ⚑. Her work in renewable energies highlights her commitment to sustainable development and green technologies 🌱. Dr. Yaghoubi also explores advanced control methods like Model Predictive Controllers (MPC) and leverages the power of artificial neural networks, machine learning, and deep learning to solve complex problems πŸ€–. Furthermore, her research extends to plasmonic and nano-electronic devices, showcasing her versatility and passion for technological advancements at the microscopic scale πŸ”¬.

Award and HonorπŸ†

Dr. Elaheh Yaghoubi has received several prestigious awards and honors in recognition of her outstanding contributions to the field of electronic and electrical engineering πŸ…. She has been lauded for her innovative research and dedication to advancing technology, earning accolades such as the Best Research Paper Award and the Excellence in Research Award πŸ₯‡. Her work in renewable energies and power management has garnered international recognition, highlighting her commitment to sustainable development 🌍. Additionally, Dr. Yaghoubi has been invited to speak at numerous conferences and workshops, where she has shared her insights and expertise with peers and emerging engineers worldwide 🌐.

Research Skills🌟

Dr. Elaheh Yaghoubi is a highly skilled researcher in electronic and electrical engineering, possessing a diverse array of technical proficiencies 🧠. Her expertise encompasses power system analysis, power system stability, and power management ⚑. She is adept in the fields of microgrids, smart grids, and renewable energies, employing advanced methodologies such as model predictive controllers (MPC) and artificial neural networks πŸ€–. Dr. Yaghoubi’s research extends to plasmonics and nano-electronic devices, where she utilizes machine learning and deep learning techniques to drive innovation πŸ”¬. Her proficiency in simulation and programming enhances her ability to develop and optimize complex power systems, making her a valuable asset in the realm of modern engineering 🌟

AchievementsπŸ…

  • πŸ† Awarded the Best Research Paper at the International Conference on Power Systems in 2022.
  • πŸ’‘ Developed an innovative model predictive controller (MPC) for smart grids, significantly enhancing power management.
  • 🌍 Led a groundbreaking study on renewable energies, contributing to sustainable energy solutions.
  • πŸ₯‡ Recognized for her exceptional work in microgrid simulation and programming.
  • πŸ› οΈ Successfully managed quality control projects for sockets, plugs, electronic shields, and cables, ensuring industry standards.
  • πŸ“š Published multiple high-impact research papers in prestigious journals, advancing knowledge in power systems and nano-electronic devices.
  • πŸ€– Pioneered the integration of artificial neural networks in power system stability analysis, leading to improved system reliability.
  • πŸ”¬ Contributed significantly to the field of plasmonics, earning accolades for her research innovations.
  • 🌟 Honored with the Outstanding Young Researcher Award by the Iranian Society of Electrical Engineers.
  • πŸ… Received multiple grants for her cutting-edge research projects on smart grids and renewable energy technologies.

ProjectsπŸ’»βš‘

  • πŸ”‹ Power System Stability Analysis: Developed advanced models to analyze and enhance the stability of power systems under various operational conditions.
  • ⚑ Microgrid and Smart Grids Simulation: Led the simulation and programming of microgrids, contributing to the development of smart grid technologies.
  • 🌞 Renewable Energy Integration: Designed and implemented systems for integrating renewable energy sources into existing power grids, promoting sustainable energy solutions.
  • πŸ’» Model Predictive Controller (MPC) Development: Created innovative MPC algorithms to optimize power management in smart grids, improving efficiency and reliability.
  • πŸ€– Artificial Neural Network Application: Applied machine learning techniques to predict and mitigate power system instabilities, enhancing overall system performance.
  • 🏠 Quality Control of Electronic Shields: Managed quality control processes for home electronic shields, ensuring compliance with industry standards.
  • πŸ”Œ Quality Control of Wires and Cables: Oversaw quality assurance projects for electrical wires and cables, maintaining high standards in manufacturing.
  • πŸ“‘ Internet of Things (IoT) and Python Training: Conducted training sessions on IoT applications and Python programming, fostering technological innovation.
  • πŸ“± Kotlin Android Apps and PHP Development: Developed Android applications using Kotlin and created dynamic web applications with PHP, showcasing versatility in software development.
  • 🌐 Plasmonic and Nano-Electronic Devices Research: Led research projects on plasmonic and nano-electronic devices, contributing to advancements in nano-technology and electronics.
Publications πŸ“š
  • Triple-channel glasses-shape nanoplasmonic demultiplexer based on multi nanodisk resonators in MIM waveguide
    • Authors: AA Faghani, E Yaghoubi, E Yaghoubi
    • Year: 2021
    • Citation: Optik 237, 166697 πŸŒπŸ”¬
  • The role of mechanical energy storage systems based on artificial intelligence techniques in future sustainable energy systems
    • Authors: M Khaleel, E Yaghoubi, E Yaghoubi, MZ Jahromi
    • Year: 2023
    • Citation: Int. J. Electr. Eng. and Sustain., 01-31 πŸ”‹πŸ€–
  • Tunable band-pass plasmonic filter and wavelength triple-channel demultiplexer based on square nanodisk resonator in MIM waveguide
    • Authors: AA Faghani, Z Rafiee, H Amanzadeh, E Yaghoubi, E Yaghoubi
    • Year: 2022
    • Citation: Optik 257, 168824 πŸ”πŸ“
  • Electric vehicles in China, Europe, and the United States: Current trend and market comparison
    • Authors: M Khaleel, Y Nassar, HJ El-Khozondar, M Elmnifi, Z Rajab, E Yaghoubi, …
    • Year: 2024
    • Citation: Int. J. Electr. Eng. and Sustain., 1-20 πŸš—πŸŒ
  • Reducing the vulnerability in microgrid power systems
    • Authors: Z Yusupov, E Yaghoubi, V Soyibjonov
    • Year: 2023
    • Citation: Science and innovation 2 (A5), 166-175 πŸ’‘πŸ”
  • 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: E Yaghoubi, E Yaghoubi, A Khamees, AH Vakili
    • Year: 2024
    • Citation: Neural Computing and Applications, 1-45 πŸ§ πŸ“Š
  • Controlling and tracking the maximum active power point in a photovoltaic system connected to the grid using the fuzzy neural controller
    • Authors: Z Yusupov, E Yaghoubi, E Yaghoubi
    • Year: 2023
    • Citation: 2023 14th International Conference on Electrical and Electronics Engineering … βš‘πŸ“
  • Modeling and Control of Decentralized Microgrid Based on Renewable Energy and Electric Vehicle Charging Station
    • Authors: Z Yusupov, N Almagrahi, E Yaghoubi, E Yaghoubi, A Habbal, D Kodirov
    • Year: 2022
    • Citation: World Conference Intelligent System for Industrial Automation, 96-102 πŸŒπŸ”‹
  • A systematic review and meta-analysis of machine learning, deep learning, and ensemble learning approaches in predicting EV charging behavior
    • Authors: E Yaghoubi, E Yaghoubi, A Khamees, D Razmi, T Lu
    • Year: 2024
    • Citation: Engineering Applications of Artificial Intelligence 135, 108789 πŸš—πŸ§