Adisu Makeyaw | Power System | Best Researcher Award

Mr. Adisu Makeyaw | Power System | Best Researcher Award

Mr. Adisu Makeyaw , Beijing Jiaotong University , China.

Adisu Makeyaw is a promising young researcher and graduate student at Beijing Jiaotong University, focusing on advanced power systems and railway electrification. With a solid background in electrical engineering and a passion for solving real-world infrastructure problems, Adisu has emerged as a dedicated contributor in the field of smart energy systems. His research has emphasized energy storage, regenerative braking, and stray current mitigation in electrified railways. Through his collaborations with industry partners like the State Grid Shanghai Electric Power Research Institute, he bridges the gap between academic theory and practical solutions for urban power system stability and efficiency.

Publication Profile

ORCID

๐ŸŽ“ Education Background

Adisu Makeyaw pursued his undergraduate and graduate education in electrical and power engineering with a specialization in railway electrification systems. Currently enrolled as a graduate student at Beijing Jiaotong University, he has developed technical expertise in modeling and simulation, especially regarding energy storage systems and control strategies. His thesis, titled โ€œResearch on Energy Storage System Scheme of Electrified Railway Traction Substation,โ€ demonstrates his capability in addressing complex engineering challenges. Throughout his academic journey, Adisu has combined analytical rigor with a focus on practical implementation, laying a strong foundation for innovative solutions in the field of sustainable energy.

๐Ÿง‘โ€๐Ÿ’ผ Professional Experience

Though still a student, Adisu Makeyaw has gained early professional recognition through impactful research collaborations. He has worked closely with the State Grid Shanghai Electric Power Research Institute, contributing to transformer DC bias mitigation solutions in metro systems. His work integrates simulation, field data, and theoretical analysis to design real-time monitoring and suppression methods. These experiences not only enhanced his engineering acumen but also strengthened his ability to manage industry-academia collaboration. Adisu continues to expand his professional portfolio by engaging in research that influences policy and technical standards in power distribution networks and urban rail infrastructure.

๐Ÿ† Awards and Honors

While formal awards are currently pending, Adisu Makeyawโ€™s academic contributions are already being acknowledged in reputable scientific platforms. His recent publication in the Energies journal showcases his innovative thinking and has gained scholarly attention. As a member (pending) of the IEEE, he is positioning himself among global professionals in electrical engineering. His impactful work in DC bias mitigation and energy storage system design reflects a commitment to research excellence that is well-aligned with recognition such as the Best Researcher Award. With growing citations and collaboration with leading institutes, Adisu is on a clear trajectory for prestigious accolades in the near future.

๐Ÿ”ฌ Research Focus

Adisuโ€™s research centers around regenerative braking, energy storage systems, stray current mitigation, and transformer DC bias phenomena within urban rail transit systems. He is especially interested in how electrified railway systems affect utility grid performance and transformer health. His projects explore innovative ways to reduce electromagnetic disturbances, enhance transformer longevity, and stabilize grid voltage under metro-induced interference. A key aspect of his work includes proposing DC-blocking devices, integrated simulation models, and optimization strategies that are grounded in both theory and practice. His current work contributes toward resilient, sustainable, and intelligent urban electrification systems.

๐Ÿงพ Conclusion

Adisu Makeyaw is a rising researcher whose work bridges the technical gaps in urban electrification and smart energy systems. With a keen eye for real-world applicability and a deep understanding of power electronics, Adisu is making meaningful contributions to infrastructure innovation. His academic rigor, combined with practical collaboration, makes him a strong contender for recognition such as the Best Researcher Award. As he continues to publish, collaborate, and innovate, Adisu stands as a promising figure in the transformation of sustainable railway systems and future-proof power networks.

๐Ÿ“„ Top Publication Note

Title: Utility Transformer DC Bias Caused by Metro Stray Currentโ€”A Review
Authors: Makeyaw, A.; Yang, X.; Sun, X.; Liu, K.; Wu, T.; Chen, L.
Journal: Energies
Published Year: 2025
Cited by Articles: 3 (as of July 2025 in Google Scholar and Scilit)
Indexed In: SCI, Scopus

Dr. Dawei Qiu | Smart Grid | Best Researcher Award

Dr. Dawei Qiu | Smart Grid | Best Researcher Award

Lecturer, University of Exeter, United Kingdom

Dr. Dawei Qiu is a distinguished scholar in smart energy systems, currently serving as a Lecturer at the University of Exeter, UK ๐Ÿซ. With a strong background in electrical engineering and power systems, he specializes in AI-driven reinforcement learning, market design for low-carbon energy transition, and resilience enhancement of energy systems โšก. His extensive research contributions in smart grids and power systems have earned him recognition in academia, with a Google Scholar citation count of 2,109, an h-index of 24, and an h10-index of 35 ๐Ÿ“Š.

Publication Profile

Google Scholar

๐ŸŽ“ Education

Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016โ€“2020) ๐ŸŽ“, where he conducted pioneering research on local flexibility’s impact on electricity retailers under the supervision of Prof. Goran Strbac. Prior to this, he completed his M.Sc. in Power System Engineering from University College London (2014โ€“2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010โ€“2014) โš™๏ธ. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.

๐Ÿ’ผ Experience

Dr. Qiu’s professional career spans academia and research institutions, where he has contributed significantly to energy systems innovation ๐ŸŒ. Before joining the University of Exeter in 2024, he was a Research Fellow at Imperial College London (2023โ€“2024), specializing in market design for low-carbon energy systems. He also served as a Research Associate at the same institution from 2020 to 2023 ๐Ÿ”ฌ. His work in smart grids and energy resilience has been instrumental in shaping sustainable and intelligent power infrastructure.

๐Ÿ† Awards and Honors

Dr. Qiuโ€™s research excellence has been acknowledged through various accolades ๐Ÿ…. His contributions to smart energy systems, AI-driven reinforcement learning, and low-carbon market design have positioned him as a leading researcher in the field. His studies have been published in top-tier journals, and his work has received high citations, demonstrating its impact on the global research community ๐ŸŒŸ.

๐Ÿ”ฌ Research Focus

Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications ๐Ÿค–. His work explores market mechanisms for cost-effective and sustainable energy transitions, as well as the resilience enhancement of energy systems in response to climate change ๐ŸŒ. His expertise in AI-driven optimization and machine learning applications in energy systems makes him a key contributor to the advancement of smart grid technologies.

๐Ÿ”š Conclusion

Dr. Dawei Qiu is a leading researcher in smart energy systems, with a strong academic background and impactful contributions to power systems engineering ๐Ÿ”ฌ. His expertise in AI-driven market optimization, reinforcement learning, and resilient energy systems has made him a valuable asset to the research community ๐ŸŒ. With his ongoing work at the University of Exeter, he continues to drive innovation in low-carbon and intelligent energy solutions โšก.

๐Ÿ”— Publications

A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hubย โ€“ Applied Energy (Under review, 2025) ๐Ÿ”— Link

Enhanced Meta Reinforcement Learning for Resilient Transient Stabilizationย โ€“ IEEE Transactions on Power Systems (Under review, 2025) ๐Ÿ”— Link

Machine learning-based economic model predictive control for energy hubs with variable energy efficienciesย โ€“ Energy (First round revision, 2024) ๐Ÿ”— Link

A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy Systemsย โ€“ Proceedings of the IEEE (Under review, 2025) ๐Ÿ”— Link

Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region Aggregationย โ€“ IEEE Transactions on Smart Grid (First round revision, 2024) ๐Ÿ”— Link

A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution Networksย โ€“ IEEE Transactions on Power Systems (Under review, 2024) ๐Ÿ”— Link

Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load Managementย โ€“ IEEE Internet of Things Journal (Under review, 2024) ๐Ÿ”— Link

Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management Strategyย โ€“ Energy (Under review, 2024) ๐Ÿ”— Link

Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement Learningย โ€“ IEEE Transactions on Network Science and Engineering (Under review, 2024) ๐Ÿ”— Link