Assoc. Prof. Dr Wei Wang | Smart Grid Systems | Best Researcher Award

Assoc. Prof. Dr Wei Wang | Smart Grid Systems | Best Researcher Award

Assoc. Prof. Dr Wei Wang | Nanjing Normal University | China

Assoc. Prof. Dr. Wei Wang, is an accomplished Associate Professor and Assistant to the Dean at the School of Electrical and Automation Engineering, Nanjing Normal University, and an IEEE Senior Member recognized for his extensive contributions to electrical engineering. Holding M.S. and Ph.D. degrees from Southeast University, his research expertise spans electromagnetic field computation, energy harvesting, and innovative wireless power transfer (WPT) systems. He has successfully led or participated in 26 research projects and 21 consultancy collaborations with industry, published 35 peer-reviewed journal papers, authored two academic books, and holds 32 patents. His research achievements are reflected in 1,165 citations by 972 documents, with 90 publications and an h-index of 19. As an editorial board member and guest editor of several international journals, Dr. Wang also serves as a guest researcher at the State Key Laboratory for Smart Grid Protection and Operation Control. His notable innovationโ€”the PPS-S topology with adjustable output power and a quasi-constant-power-constant-voltage (QCP-CV) charging strategyโ€”addresses the limitations of conventional WPT systems by achieving zero-voltage-switching (ZVS) while maintaining power stability around 65 W and reducing power fluctuation by 80% under varying loads. His pioneering work has earned him prestigious honors, including the Second Prize for Scientific Research and Technological Invention from the Ministry of Education and a Gold Award at the 2023 Geneva International Invention Exhibition, solidifying his impact in advanced power transfer technologies.

Profile: Scopus

Featured Publications

Wang, W. (2025). Research on self-powered high precision voltage measurement technology for the power lines based on the inversion of electric field. Zhongguo Dianji Gongcheng Xuebao Proceedings of the Chinese Society of Electrical Engineering.

Wang, W. (2025). Regulation strategy of impact response of regional integrated energy system based on ultra short term prediction. Journal of Electrical Engineering China.

Wang, W. (2025). Optimized constant power charging of PT-symmetry-based three-coil WPT system. Conference Paper.

Wang, W. (2025). Analysis and optimization of energy harvesting characteristics of converter valve magnetic field self-powered harvester. Electric Power Engineering Technology.

Wang, W. (2025). Extended effective distance of PT-symmetry-based double-coil WPT system. Conference Paper.

Wang, W. (2025). Quasi-constant power wireless charging strategy based on power adjustable PPS-S topology. Journal of Power Electronics.

Dr. Aamir Ali | Smart Grid Systems | Best Researcher Award

Dr. Aamir Ali | Smart Grid Systems | Best Researcher Award

Dr. Aamir Ali | Quaid-e-Awam University of Engineering Science and Technology | Pakistan

Dr. Aamir Ali is currently serving as an Assistant Professor (BPS-19) in the Department of Electrical Engineering at Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan. He is a highly dedicated academic and researcher specializing in power system planning and optimization, distributed generation, and microgrid operations in both islanded and grid-connected modes. Dr. Ali earned his Ph.D. in Electrical Engineering from QUEST in 2020, where his doctoral research focused on single and multi-objective mathematical programming, direct search evolutionary algorithms, and optimization techniques for economic dispatch, optimal power flow, and unit commitment with renewable energy integration such as wind and solar PV systems. Prior to his doctorate, he completed his Master of Engineering in Power System Optimization from the same institution in 2015 and his Bachelor of Engineering in Electrical Power with an outstanding 85% score in 2012. His academic journey began with strong foundational performance at the intermediate and matriculation levels, both from the Board of Intermediate and Secondary Education, Hyderabad, Sindh, where he secured first division and A-1 grade distinctions. With 445 citations by 342 documents, 27 published works, and an h-index of 11, Dr. Aamir Ali has established himself as an active researcher in power systems optimization. He aspires to continue contributing to academia and research while leading a top-tier institution toward excellence in education and innovation.

Profile: Scopus | Orcid

Featured Publications

Akbar Talani, R., Kaloi, G. S., Ali, A., Abbas, G., Emara, A., & Touti, E. (2025, July 29). Fault analysis and performance improvement of grid-connected doubly fed induction generator through an enhanced crowbar protection scheme. PLOS One.

Ali, A., Akbar Talani, R., Kaloi, G. S., Bijarani, M. A., Abbas, G., Hatatah, M., Mercorelli, P., & Touti, E. (2025, January 29). Dynamic performance analysis and fault ride-through enhancement by a modified fault current protection scheme of a grid-connected doubly fed induction generator. Machines, 13(2).

Ali, A., Ali, A., Liu, Z., Abbas, G., Touti, E., & Nureldeen, W. (2024). Dynamic multi-objective optimization of grid-connected distributed resources along with battery energy storage management via improved bidirectional coevolutionary algorithm. IEEE Access.

Ali, A., Shah, A., Keerio, M. U., Mugheri, N. H., Abbas, G., Touti, E., Hatatah, M., Yousef, A., & Bouzguenda, M. (2024). Multi-objective security constrained unit commitment via hybrid evolutionary algorithms. IEEE Access.

Abbas, G., Wu, Z., & Ali, A. (2024, December). A two-stage reactive power optimization method for distribution networks based on a hybrid model and data-driven approach. IET Renewable Power Generation.

Ali, A., Aslam, S., Mirsaeidi, S., Mugheri, N. H., Memon, R. H., Abbas, G., & Alnuman, H. (2024, December). Multi-objective multiperiod stable environmental economic power dispatch considering probabilistic wind and solar PV generation. IET Renewable Power Generation.

Dr. Mingwei Zhao | Electrical Engineering | Excellence in Research Award

Dr. Mingwei Zhao | Electrical Engineering | Excellence in Research Award

Dr. Mingwei Zhao , Jiangsu Normal University & Shanghai University , China.

Dr. Mingwei Zhao ๐ŸŽ“, born in Shandong, China ๐Ÿ‡จ๐Ÿ‡ณ, is a dedicated researcher and educator in the field of electrical engineering โšก. He currently serves as a Lecturer at Jiangsu Normal University ๐Ÿซ, specializing in power electronics and robotic systems ๐Ÿค–. With a strong foundation in mechanical and electrical integration ๐Ÿ”ง, he pursued advanced studies in power drive systems and control science ๐ŸŽ›๏ธ. His ongoing research is focused on innovative power electronic drive technologies and intelligent robotics ๐Ÿ’ก. Dr. Zhao’s work contributes significantly to automation and energy efficiency solutions in modern engineering ๐ŸŒ.

Professional Profile

Scopus

Education & Experience

  • ๐ŸŽ“ B.S. in Mechanical and Electrical Integration, Nanjing University of Science and Technology, 2004

  • ๐ŸŽ“ M.S. in Power Electronics and Power Drive, Nanjing University of Aeronautics and Astronautics, 2012

  • ๐ŸŽ“ Ph.D. (in progress) in Control Science and Engineering, Shanghai University, since 2016

  • ๐Ÿ‘จโ€๐Ÿซ Lecturer, School of Electrical Engineering and Automation, Jiangsu Normal University

Summary Suitability

Dr. Mingwei Zhao is a highly dedicated and innovative researcher, making him a strong candidate for the Excellence in Researcher Award. With a solid academic foundation and over a decade of hands-on experience, Dr. Zhao has significantly advanced the fields of power electronics drive technologies and robotic systems through both applied research and academic leadership.

Professional Development

Dr. Zhao has continually expanded his expertise through rigorous academic pursuits and hands-on teaching experience ๐Ÿ‘จโ€๐Ÿ”ฌ. Currently undertaking his Ph.D. at Shanghai University ๐ŸŽ“, he stays at the forefront of technological innovation by integrating control systems and robotics into his curriculum ๐Ÿค–๐Ÿ“˜. His involvement in both academic and applied research ensures that his contributions are both theoretically sound and practically relevant ๐Ÿ› ๏ธ. As a Lecturer, he mentors students and fosters a dynamic learning environment ๐ŸŽค๐Ÿ’ก. His professional development reflects a balanced focus on research, teaching, and practical implementation in modern automation systems ๐Ÿš€.

Research Focus

Dr. Zhaoโ€™s research is centered in the Electrical and Automation Engineering category โš™๏ธ, with a specialized emphasis on power electronic drive systems โšก and robotic control integration ๐Ÿค–. He explores the design and control of energy-efficient power systems, automation technology, and intelligent robotic operations ๐Ÿ”‹๐Ÿ”. His current studies contribute to advancing smart drive technologies that are vital for automation and Industry 4.0 initiatives ๐Ÿญ๐Ÿ’ก. By leveraging multidisciplinary principles, he aims to develop sustainable and intelligent engineering systems that enhance the performance and adaptability of electrical devices ๐ŸŒฑ๐Ÿง .

Publication Top Notes

  • Title:
    An Open-Circuit Fault Diagnosis for Three-Phase PWM Rectifier Without Grid Voltage Sensor Based on Phase Angle Partition

  • Authors:
    Mingwei Zhao, et al.

  • Journal:
    IEEE Transactions on Circuits and Systems I: Regular Papers

  • Publisher:
    IEEE (Institute of Electrical and Electronics Engineers)

  • Year:
    2024

  • Citations:
    4 (as of the latest count)

  • Summary:
    This article presents a fault diagnosis method for three-phase PWM rectifiers that eliminates the need for a grid voltage sensor. It uses phase angle partitioning to detect open-circuit faults efficiently, enhancing system reliability.

Conclusion

Dr. Zhaoโ€™s pioneering efforts and sustained contributions to power electronics and robotics make him a worthy nominee for the Excellence in Researcher Award. His blend of theoretical expertise, practical engineering solutions, and educational leadership continues to push the boundaries of automation and intelligent systems, benefiting both academia and industry.