Mohammad Parhamfar | Engineering | Best Researcher Award

Published on by Global Scholar Awards

Dr. Mohammad Parhamfar | Engineering | Best Researcher Award

www.parhamfar.com, Iran

Dr. Mohammad Parhamfar is a distinguished renewable energy expert and electrical engineer specializing in solar energy, with 19 years of experience spanning software development, electrical engineering, and sustainable energy solutions. Holding a Doctor of Business Administration (DBA) and a Master’s in Renewable Energy, he has contributed significantly to the field through over 40 published papers, eight authored books, and multiple patents in electrical software design and lightning protection for solar farms. As a leader in solar project development, he has designed 50 MW solar projects, implemented 1 MW rooftop systems, and played a key role in Iran’s first 10 MW solar power plant. He has received numerous awards, including the 2023 Creative Researcher Award, and serves on the editorial boards of various energy-related journals. His innovations in energy management, microgrids, and carbon trading, along with his active participation in international conferences, cement his reputation as a pioneering researcher and industry leader.

Professional Profile 

Education

Dr. Mohammad Parhamfar holds a Doctor of Business Administration (DBA), a Master’s degree in Renewable Energy, and a Bachelor’s degree in Electrical Engineering. His multidisciplinary educational background integrates technical expertise with strategic business management, enabling him to drive innovation in renewable energy and electrical engineering. His academic journey has equipped him with deep knowledge in solar energy systems, electrical installations, and energy management. He has also obtained numerous technical certifications in solar designing, energy auditing, microgrids, and IEEE teaching standards, further strengthening his expertise in sustainable energy solutions. His commitment to education extends beyond personal learning, as he has actively contributed to academia as a lecturer in solar energy, sharing his knowledge with students and professionals. Dr. Parhamfar’s strong academic foundation, coupled with practical experience, has positioned him as a leader in the field, allowing him to contribute significantly to large-scale solar projects, research, and policy development.

Professional Experience

Dr. Mohammad Parhamfar boasts an extensive professional career spanning over 19 years in renewable energy, electrical engineering, and software development. He has held key leadership positions, including CEO of Yeganeh Energy, where he managed the implementation of solar projects, and CTO of Applebone Company, specializing in solar energy and IT solutions. Dr. Parhamfar has led the development of large-scale solar projects, including designing a 50 MW solar system and coordinating the first 10 MW solar power plant in Iran. He has also served as a project manager and electrical engineer for various high-profile projects, such as the 1000 MW solar farm in Isfahan and multiple international solar initiatives in Armenia and Oman. As a freelancer, he has provided consulting services to several organizations, contributing his expertise in renewable energy, electrical systems design, and project management. His work has earned him recognition as a leader in the renewable energy sector.

Research Interest

Dr. Mohammad Parhamfar’s research interests lie at the intersection of renewable energy, electrical engineering, and sustainable development. His primary focus is on solar energy systems, particularly the design, implementation, and optimization of large-scale solar projects. He is also deeply involved in the integration of artificial intelligence with renewable energy solutions to enhance efficiency and performance. Dr. Parhamfar is passionate about addressing climate change through sustainable energy practices, with research extending into carbon trading and energy management strategies. He has explored innovative topics like lightning protection systems, grounding techniques for solar farms, and the development of electrical software for energy systems. His contributions to the renewable energy field include pioneering projects such as the first low-energy government building in Isfahan and the world’s first lightning risk assessment software for solar power plants. Additionally, Dr. Parhamfar is committed to exploring microgrid technology and its role in optimizing energy distribution and reducing environmental impacts.

Award and Honor

Dr. Mohammad Parhamfar has received numerous prestigious awards and honors for his groundbreaking contributions to renewable energy and electrical engineering. In 2023, he was recognized as a Creative Researcher by the International Academic Achievements and Award for his innovative work in solar energy. His remarkable achievements have also earned him recognition as the Best Innovative Engineer in 2013 in Isfahan and the Best Author in Modern Technology Journal in 2024. Dr. Parhamfar’s excellence in solar energy and engineering was further acknowledged when he ranked first in his Master’s program in Renewable Energy. He has also received accolades for his contributions to the energy sector, including being selected for his pioneering work on solar power plant insurance in Iran. His extensive involvement in research and development has earned him a reputation as a leading expert in renewable energy and a recipient of several honors for his contributions to technology and sustainability.

Research Skill

Dr. Mohammad Parhamfar possesses exceptional research skills that blend technical expertise with innovative problem-solving in the fields of renewable energy, electrical engineering, and energy management. His extensive experience in solar energy systems has enabled him to lead and contribute to cutting-edge research projects, particularly in the areas of solar power plant design, lightning protection systems, and energy optimization. Dr. Parhamfar’s research skills are demonstrated through his ability to apply complex concepts such as artificial intelligence to renewable energy solutions, enhancing the efficiency and effectiveness of energy systems. He is adept at utilizing software development tools to create groundbreaking solutions like the world’s first lightning risk assessment software for solar plants. Additionally, his ability to collaborate across multidisciplinary teams and lead large-scale research initiatives has made him a key figure in the energy sector. His research is marked by creativity, practical application, and a strong commitment to sustainable energy solutions.

Conclusion

Mohammad Parhamfar is highly suitable for the Best Researcher Award, particularly in Renewable Energy and Electrical Engineering. His strong research portfolio, industry contributions, patents, and leadership roles make him a leading figure in his field. Strengthening his academic publication impact, securing more international research funding, and increasing global collaborations would further enhance his competitiveness for the award.

Publications Top Noted

  • Title: Towards the application of renewable energy technologies in green ports: Technical and economic perspectives
    Authors: AMA Mohammad Parhamfar, Iman Sadeghkhani
    Year: 2023
    Citation: IET Renewable Power Generation, Volume 37
  • Title: EMPOWERING THE GRID: TOWARD THE INTEGRATION OF ELECTRIC VEHICLES AND RENEWABLE ENERGY IN POWER SYSTEMS
    Authors: MP Alireza Zabihi
    Year: 2024
    Citation: International Journal of Energy Security and Sustainable Energy (IJESSE), Volume 23
  • Title: Towards the net zero carbon future: A review of blockchain‐enabled peer‐to‐peer carbon trading
    Authors: M Parhamfar, I Sadeghkhani, AM Adeli
    Year: 2024
    Citation: Energy Science & Engineering, Volume 12, Issue 3, Pages 1242-1264
  • Title: Increase power output and radiation in photovoltaic systems by installing mirrors
    Authors: A Zabihi, M Parhamfar, SS Duvvuri, M Abtahi
    Year: 2024
    Citation: Measurement: Sensors, Volume 31, Article 100946
  • Title: Lightning Risk Assessment Software Design for Photovoltaic Plants in Accordance with IEC 62305-2
    Authors: M Parhamfar
    Year: 2022
    Citation: Energy System Research, Volume 5, Issue 2, Page 21
  • Title: Frequency and Time Series Analysis of Surge Arrester in Power Distribution Systems
    Authors: A Zabihi, M Parhamfar
    Year: 2024
    Citation: Advances in Engineering and Intelligence Systems, Volume 3, Issue 03, Pages 94-103
  • Title: A Light Weight Mobile Net SSD Algorithm based identification and Detection of Multiple Defects in Ceramic Insulators
    Authors: NB Mohammad Parhamfar, P. Bhavya Sree, K. Balaji
    Year: 2024
    Citation: Journal of Modern Technology, Volume 1, Issue 1, Pages 59-74
  • Title: Towards Green Airports: Factors Influencing Greenhouse Gas Emissions and Sustainability through Renewable Energy
    Authors: M Parhamfar
    Year: 2024
    Citation: Next Research, Article 100060
  • Title: Feasibility Study and Design of Smart Low-Energy Building Electrical Installations (Case Study: Isfahan University, Virtual Faculty Building)
    Authors: SS Mohammad Parhamfar
    Year: 2023
    Citation: Energy Systems Research Journal, Volume 6, Issue 3, Pages 57-74
  • Title: The Study of Electrical Grid Components After Installing a 10 MW Photovoltaic Power Plant with Large-Scale Batteries at Peak Load by DigSilent Software
    Authors: AA Mohammad Parhamfar
    Year: 2022
    Citation: American Journal of Electrical Power and Energy Systems, Volume 11, Issue 5, Pages 97-107

Masoud Yaghini | Engineering | Best Researcher Award

Published on by Global Scholar Awards

Assoc Prof Dr Masoud Yaghini | Engineering | Best Researcher Award

Faculty Member at Iran University of Science and Technology, Iran

Dr. Masoud Yaghini is a distinguished faculty member in the Department of Rail Transportation at the Iran University of Science and Technology. Born on December 8, 1966, he holds an extensive academic and professional background in rail transportation planning and optimization techniques. With over two decades of experience, Dr. Yaghini has made substantial contributions to the fields of transportation logistics, network design, and data mining, particularly within the railway industry. His innovative approaches to complex rail transportation problems have earned him a reputation as a leading researcher in the field. Dr. Yaghini is widely published and continues to shape the future of transportation with cutting-edge research.

Professional Profile

Education

Dr. Yaghini received his Ph.D. in Rail Transportation Planning and Engineering from Northern Jiaotong University, Beijing, China, in 2003, with a focus on dynamic service network design. He also holds an MSc and BSc in Industrial Management from Islamic Azad University, Tehran. His master’s thesis on resource assignment optimization in preventive maintenance laid the foundation for his interest in large-scale optimization problems. Additionally, he furthered his knowledge with specialized training in Ergonomics and Human Factors for Railways from the University of Birmingham, UK, in 2005. This diverse educational background has equipped Dr. Yaghini with both theoretical and practical expertise in optimizing transportation systems.

Professional Experience

Dr. Yaghini has over 20 years of professional experience, primarily as a faculty member at the Iran University of Science and Technology. He teaches a wide range of courses, from advanced computer programming to railway operations management and data mining in transportation. His professional experience extends beyond academia into consultancy work in optimization and transportation planning. Dr. Yaghini has also conducted numerous short courses and workshops in data mining, information management, and metaheuristic algorithms for both academic institutions and private companies. His role as an educator and consultant has allowed him to bridge the gap between academic research and real-world transportation challenges.

Research Interests

Dr. Yaghini’s research primarily focuses on optimization problems in rail transportation, including train scheduling, fleet sizing, and locomotive scheduling. He has a strong interest in metaheuristics such as Genetic Algorithms, Tabu Search, and Ant Colony Optimization, as well as exact solution methods like Column Generation and Branch and Cut. His work also explores data mining techniques applied to railway systems, such as the prediction of train delays and analysis of accident data. His research is driven by the need to optimize and improve efficiency in transportation systems, particularly in large-scale rail networks. His work has significant practical implications for enhancing railway operations and minimizing costs.

Awards and Honors

Dr. Yaghini’s contributions to transportation research have earned him multiple accolades, though his recognition mainly stems from his published works in high-impact journals such as Applied Mathematical Modelling and Journal of Transportation Engineering. He has been recognized for his work on solving complex railway optimization problems through innovative algorithms like Ant Colony Optimization and Simulated Annealing. In addition to his publications, Dr. Yaghini has been invited to present his findings at numerous international conferences. While he has not widely publicized any specific awards, his ongoing research contributions have earned him a solid reputation in the global transportation research community, marking him as a key figure in rail transportation planning and optimization.

Conclusion

Dr. Masoud Yaghini’s research portfolio is impressive, with a strong emphasis on rail transportation and optimization problems. His consistent contributions to both academic knowledge and practical railway systems demonstrate his potential for recognition as a top researcher. By broadening his collaborative network and impact beyond academia, he could further strengthen his candidacy for prestigious awards like the Best Researcher Award.

Publication top noted

  1. Online prediction of arrival and departure times in each station for passenger trains using machine learning methods
    • Vafaei, S., Yaghini, M.
    • Transportation Engineering, 2024
    • 📖 0 citations
  2. Analysis of the relationship between geometric parameters of railway track and twist failure by using data mining techniques
    • Izadi Yazdan Abadi, E., Khadem Sameni, M., Yaghini, M.
    • Engineering Failure Analysis, 2023
    • 📖 2 citations
  3. A mathematical formulation and an LP-based neighborhood search matheuristic solution method for the integrated train blocking and shipment path problem
    • Yaghini, M., Mirghavami, M., Zare Andaryan, A.
    • Networks, 2021
    • 📖 5 citations
  4. Efficient algorithms to minimize makespan of the unrelated parallel batch-processing machines scheduling problem with unequal job ready times
    • Zarook, Y., Rezaeian, J., Mahdavi, I., Yaghini, M.
    • RAIRO – Operations Research, 2021
    • 📖 10 citations
  5. An adaptive structure on a new local branching algorithm using instantaneous dimensions and convergence speed: a case study for multi-commodity network design problems
    • Hajiyan, H., Yaghini, M.
    • SN Applied Sciences, 2020
    • 📖 1 citation
  6. Optimization of embedded rail slab track with respect to environmental vibrations
    • Esmaeili, M., Yaghini, M., Moslemipour, S.
    • Scientia Iranica, 2020
    • 📖 0 citations
  7. An Effective Improvement to Main Non-periodic Train Scheduling Models by a New Headway Definition
    • Jafarian-Moghaddam, A.R., Yaghini, M.
    • Iranian Journal of Science and Technology – Transactions of Civil Engineering, 2019
    • 📖 2 citations
  8. Optimizing headways for urban rail transit services using adaptive particle swarm algorithms
    • Hassannayebi, E., Zegordi, S.H., Amin-Naseri, M.R., Yaghini, M.
    • Public Transport, 2018
    • 📖 26 citations
  9. Train timetabling at rapid rail transit lines: a robust multi-objective stochastic programming approach
    • Hassannayebi, E., Zegordi, S.H., Amin-Naseri, M.R., Yaghini, M.
    • Operational Research, 2017
    • 📖 48 citations
  10. Timetable optimization models and methods for minimizing passenger waiting time at public transit terminals
  • Hassannayebi, E., Zegordi, S.H., Yaghini, M., Amin-Naseri, M.R.
  • Transportation Planning and Technology, 2017
  • 📖 35 citations