Dr. Dawei Qiu | Smart Grid | Best Researcher Award

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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 🏫. 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 ⚡. 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 📊.

Publication Profile

Google Scholar

🎓 Education

Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016–2020) 🎓, 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 (2014–2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010–2014) ⚙️. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.

💼 Experience

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

🏆 Awards and Honors

Dr. Qiu’s research excellence has been acknowledged through various accolades 🏅. 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 🌟.

🔬 Research Focus

Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications 🤖. 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 🌍. 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.

🔚 Conclusion

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

🔗 Publications

A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hub – Applied Energy (Under review, 2025) 🔗 Link

Enhanced Meta Reinforcement Learning for Resilient Transient Stabilization – IEEE Transactions on Power Systems (Under review, 2025) 🔗 Link

Machine learning-based economic model predictive control for energy hubs with variable energy efficiencies – Energy (First round revision, 2024) 🔗 Link

A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy Systems – Proceedings of the IEEE (Under review, 2025) 🔗 Link

Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region Aggregation – IEEE Transactions on Smart Grid (First round revision, 2024) 🔗 Link

A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution Networks – IEEE Transactions on Power Systems (Under review, 2024) 🔗 Link

Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load Management – IEEE Internet of Things Journal (Under review, 2024) 🔗 Link

Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management Strategy – Energy (Under review, 2024) 🔗 Link

Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement Learning – IEEE Transactions on Network Science and Engineering (Under review, 2024) 🔗 Link

Dr. Caixin Yan | Power System Optimization | Best Researcher Award

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Dr. Caixin Yan | Power System Optimization | Best Researcher Award

PhD Student, Central South University, China

Dr. Caixin Yan is a distinguished researcher at the National Engineering Research Centre of Advanced Energy Storage Materials in Changsha, China. With a deep passion for energy systems and artificial intelligence applications in power grids, Dr. Yan has contributed significantly to the field of energy optimization and power market strategies. His expertise in reinforcement learning and grid stability has made him a prominent figure in the domain of advanced energy storage and smart grid technologies.

Publication Profile

ORCID

🎓 Education:

Dr. Yan pursued his higher education in automation and electrical engineering, focusing on intelligent power grid management and optimization. His academic journey has equipped him with extensive knowledge in multi-energy systems, deep reinforcement learning, and industrial load flexibility.

💼 Experience:

Currently associated with the National Engineering Research Centre of Advanced Energy Storage Materials, Dr. Yan has also collaborated with institutions like the School of Automation at Central South University and the Hunan Xiangjiang Artificial Intelligence Academy. His research focuses on optimizing power systems through artificial intelligence and developing cutting-edge solutions for market-based power regulation.

🏆 Awards and Honors:

While specific awards and honors are not listed, Dr. Yan’s impactful contributions to energy storage, power market strategies, and reinforcement learning applications have been recognized through his publications and collaborations. His research is gaining traction, as evidenced by his growing citation count.

🔍 Research Focus:

Dr. Yan’s research revolves around power grid optimization, energy storage integration, and AI-driven solutions for smart grids. His work on hierarchical reinforcement learning for power grid topology regulation and multi-energy systems operation strategies has been instrumental in advancing the field of intelligent energy management.

🔚 Conclusion:

Dr. Caixin Yan is a rising expert in energy storage and AI-driven power grid optimization. His contributions to power market strategies, reinforcement learning applications, and energy system integration are paving the way for a smarter and more efficient electricity landscape. With growing recognition and impactful research, he continues to make significant strides in the field of intelligent energy solutions. 🚀

📚 Publications :

Review of Power Market Optimization Strategies Based on Industrial Load Flexibility – Analyzing the role of industrial flexibility in power markets.

Power Grid Topology Regulation Method Based on Hierarchical Reinforcement Learning – Exploring AI-driven strategies for grid topology adjustments.

Deep Reinforcement Learning for Strategic Bidding in Incomplete Information Market – Applying AI to strategic bidding in uncertain energy markets.

Optimal Operation Strategies of Multi-Energy Systems Integrated with Liquid Air Energy Storage Using Information Gap Decision Theory – Investigating operational strategies for multi-energy systems.

Load Frequency Control of Photovoltaic Generation-Integrated Multi-Area Interconnected Power Systems Based on Double Equivalent-Input-Disturbance Controllers – Developing control mechanisms for PV-integrated power systems.

Prof. Dr. luiz Rodrigues | Smart Grids | Best Researcher Award

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Prof. Dr. luiz Rodrigues | Smart Grids | Best Researcher Award

Associate Professor, Federal University of Maranhao, Brazil

Dr. Luiz Henrique Neves Rodrigues is an accomplished electrical engineer, researcher, and professor with over 29 years of expertise in power systems, infrastructure project management, and smart cities. He is currently an Assistant Professor at the Federal University of Maranhão (UFMA), where he teaches interdisciplinary courses in civil, mechanical, electrical, and computing engineering. His career spans academia, industry, and research, contributing to alternative energy projects, geoinformation technologies, and telecommunications. His research focuses on the integration of smart power grids and smart city platforms using advanced communication technologies.

Publication Profile

Google Scholar

🎓 Education

Dr. Rodrigues holds a Doctorate in Mathematics and Statistics from the University of São Paulo (USP), where he specializes in smart cities and power systems. He earned his Master’s degree in Geodesic Sciences and Geoinformation Technologies from the Federal University of Pernambuco (UFPE). Additionally, he completed an MBA in Business Management from Fundação Getúlio Vargas (FGV) and pursued specialized studies in alternative energy at UFPE.

💼 Experience

Dr. Rodrigues has held key roles in academia and industry. Since 2010, he has been a professor at UFMA, where he teaches computational design, applied electricity, and digital circuits. He has contributed to specialized courses in field engineering, ports, and oil & gas. Previously, he managed engineering projects at Cura Nativus Ltda and PR2 Engenharia Ltda, overseeing alternative energy parks, wind farm development, and infrastructure projects. He also worked extensively in telecommunications and geoinformatics, holding leadership positions at Amazônia Celular, TELEPARÁ, and LH Teleinformatics, where he managed network expansion, georeferenced cadastre, and ICT hardware training.

🏆 Awards and Honors

Dr. Rodrigues has been recognized for his contributions to electrical engineering, smart cities, and geoinformation technologies. He has played a key role in developing energy-efficient systems, alternative energy solutions, and strategic planning for infrastructure projects. His work in smart grids and digital instrumentation in education has been widely acknowledged.

🔬 Research Focus

Dr. Rodrigues’ research revolves around power systems, smart grids, and the integration of smart cities with massive machine-type communication (mMTC). His work emphasizes geospatial data analysis, digital instrumentation, and computational design to optimize energy efficiency and infrastructure management. He has also explored active learning methodologies in electrical instrumentation education using virtual platforms like LabVIEW and ELVIS II.

📚 Publications

Co-Simulation of Interconnection Between Smart Power Grid and Smart Cities Platform via Massive Machine-Type Communication – (Publication details not provided).

Metodologias ativas na educação de instrumentação eletrônica utilizando plataforma de instrumentação virtuais com base em LabVIEW e ELVIS II

Conclusion

Dr. Luiz Henrique Neves Rodrigues continues to contribute significantly to the fields of power systems, smart cities, and geoinformation technologies. His academic and industrial expertise bridges the gap between engineering education, sustainable infrastructure development, and advanced computational systems, making him a leading figure in his domain. 🚀

Mr. Jaswant Singh | Energy Technologies | Best Researcher Award

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Mr. Jaswant Singh | Energy Technologies | Best Researcher Award

Lecturer, Government Polytechnic Chhachha Bhogaon Mainpuri, India

Jaswant Singh is an accomplished academician and researcher in the field of Electrical Engineering. Currently serving as a Lecturer in the Electrical Engineering Department at Government Polytechnic Chhachha Bhogaon, Mainpuri (UP) since 2021, he has been actively contributing to the domain of power electronics, drives, and electrical machines. With over a decade of teaching and research experience, he has held significant positions in reputed institutions across India. His dedication to advancing knowledge is reflected in his extensive research contributions and leadership roles in academia.

Publication Profile

🎓 Education

Jaswant Singh is presently pursuing his Ph.D. in Electrical Engineering from Dr. A.P.J. Abdul Kalam Technical University, Lucknow, India. He holds an M.Tech. in Power Electronics & Drives from Kamla Nehru Institute of Technology (KNIT), Sultanpur, which he completed in 2011. His academic journey began with a B.Tech. degree in Electrical Engineering from Uttar Pradesh Technical University (UPTU) in 2009. His strong educational foundation has fueled his research and teaching endeavors.

💼 Experience

Jaswant Singh has a rich professional background, having served in multiple institutions in various capacities. He began his teaching career in 2011 as an Assistant Professor & Head at P.K. Institute of Technology & Management, Mathura. Later, he joined Shri Ram Group of Colleges (SRGC), Muzaffarnagar, as an Assistant Professor & Head in 2012. From 2015 to 2018, he worked as an Assistant Professor at Arya College of Engineering & IT, Jaipur. He also contributed as an Assistant Professor at Rajkiya Engineering College (REC), Ambedkar Nagar, from 2018 to 2020 before taking up his current role.

🏆 Awards and Honors

Jaswant Singh has earned recognition for his research contributions in power electronics and drives. His membership in IEEE highlights his commitment to professional development and staying updated with global advancements in electrical engineering. His scholarly achievements and research publications have been well-received in academic and industrial communities.

🔬 Research Focus

His primary research interests include power electronics & drives, power operation systems, and power quality issues. He has contributed significantly to the field through his work on control and simulation of electrical machines, MPPT techniques for solar energy, and microgrid management. His research aims to optimize power systems for enhanced efficiency and sustainability.

📚 Publications

Performance Evaluation of LMPO-Based MPPT Technique for Two-Stage GIPV System with LCL Under Various Meteorological Conditions – Processes (2025) [🔗 DOI: 10.3390/pr13030849]

Issues and Challenges of Latest Green Energy Technology – Applied Artificial Intelligence (2022) [🔗 EID: 2-s2.0-85146140459]

Comparative Analysis of MPPT Control Techniques – Frontiers in Energy Research (2022) [🔗 DOI: 10.3389/fenrg.2022.856702]

Recent Control Techniques and Management of AC Microgrids – International Transactions on Electrical Energy Systems (2021) [🔗 DOI: 10.1002/2050-7038.13035]

Performance Investigation of PMSM Drive Using Vector Controlled Technique – ICPES (2012) [🔗 DOI: 10.1109/icpces.2012.6508040]

Investigation of PMSM Drives Using DTC-SVPWM Technique – IEEE SCES (2012) [🔗 DOI: 10.1109/sces.2012.6199092]

Improvement of Power Factor and Harmonics Reduction in Induction Motors – SEISCON (2011) [🔗 DOI: 10.1049/cp.2011.0419]

Performance Evaluation of Direct Torque Control with PMSM – SAMRIDDHI Journal (2011) [🔗 DOI: 10.18090/samriddhi.v2i2.1602]

🔚 Conclusion

Jaswant Singh’s academic journey is marked by his unwavering commitment to teaching, research, and innovation in electrical engineering. His extensive contributions in power electronics, renewable energy, and control systems demonstrate his expertise in the field. As an active researcher and educator, he continues to inspire students and contribute to cutting-edge technological advancements. 🚀

Jian Sun | Smart Grid Control | Best Researcher Award

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Assoc. Prof. Dr. Jian Sun | Smart Grid Control | Best Researcher Award

Associate Professor, Southwest University, China

Jian Sun is an Associate Professor in the School of Electronic and Information Engineering at Southwest University, Chongqing, China. With a strong academic and research background in automation and electrical engineering, his work focuses on control systems, reinforcement learning, and grid frequency regulation. Over the years, he has made significant contributions to the field through his publications and innovative approaches to tackling complex power grid challenges. 📚🔬

Publication Profile

ORCID

Education

Jian Sun earned his Ph.D. in Automation from Chongqing University in December 2014. He also completed a visiting Ph.D. program at the University of Wisconsin-Madison, USA, in 2014, specializing in Electrical and Computer Engineering. Prior to his doctoral studies, he obtained a Master’s degree in Automation and a Bachelor’s degree in the same field from Chongqing University. 🎓🌍

Experience

Jian Sun has extensive academic and research experience, currently serving as an Associate Professor at Southwest University. His expertise spans areas like frequency regulation in power systems, energy storage systems, and adaptive control techniques. He has published numerous papers in prestigious journals and has contributed to several interdisciplinary research projects. His work often combines advanced reinforcement learning techniques with cyber-physical systems. 💼🔧

Awards and Honors

Throughout his career, Jian Sun has received recognition for his outstanding research and contributions to the field. His work has been widely cited and appreciated by both academic and industry professionals. He continues to push the boundaries of research in smart grids, energy management, and reinforcement learning. 🏆📈

Research Focus

Jian Sun’s research focuses on developing adaptive and resilient control strategies for smart grids, particularly in the context of frequency regulation. His work includes the integration of Vehicle-to-Grid (V2G) technologies, reinforcement learning for DoS attack resilience, and advanced control systems for energy-efficient power grids. He aims to improve the stability and security of power systems in the face of cyber threats and dynamic load conditions. ⚡🧠

Conclusion

Jian Sun’s academic journey and research have contributed to advancements in smart grid technology, power system regulation, and control theory. His continued dedication to addressing critical challenges in energy systems positions him as a leading figure in his field. His research aims to make power systems smarter, more efficient, and resilient to emerging threats. 🌐🔋

Publications 

Load Forecasting for Commercial Buildings Using BiLSTM–Transformer Network and Cyber–Physical Cognitive Control Systems
Published Year: 2024
Journal: Symmetry
Cited by: Crossref

An Adaptive V2G Capacity-Based Frequency Regulation Scheme With Integral Reinforcement Learning Against DoS Attacks
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Cooperative Grid Frequency Control Under Asymmetric V2G Capacity via Switched Integral Reinforcement Learning
Published Year: 2024
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Resilient Frequency Regulation for DoS Attack Intensity Adaptation via Predictive Reinforcement V2G Control Learning
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Safe Online Integral Reinforcement Learning for Control Systems via Controller Decomposition
Published Year: 2023
Journal: Arabian Journal for Science and Engineering
Cited by: Crossref

A DoS Attack-Resilient Grid Frequency Regulation Scheme via Adaptive V2G Capacity-Based Integral Sliding Mode Control
Published Year: 2023
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

A DoS Attack Intensity-Aware Adaptive Critic Design of Frequency Regulation for EV-Integrated Power Grids
Published Year: 2023
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Structural Scheduling of Transient Control Under Energy Storage Systems by Sparse-Promoting Reinforcement Learning
Published Year: 2022
Journal: IEEE Transactions on Industrial Informatics
Cited by: Crossref

A Sparse Neural Network-Based Control Structure Optimization Game under DoS Attacks for DES Frequency Regulation of Power Grid
Published Year: 2019
Journal: Applied Sciences
Cited by: Crossref

A Stable Distributed Neural Controller for Physically Coupled Networked Discrete-Time System via Online Reinforcement Learning
Published Year: 2018
Journal: Complexity
Cited by: Crossref

Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs
Published Year: 2017
Journal: Applied Sciences
Cited by: Crossref

 

Sisil Kumarawadu | Energy systems applications | Excellence in Innovation

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Prof. Sisil Kumarawadu | Energy systems applications | Excellence in Innovation

Senior Professor, University of Moratuwa, Sri Lanka

Sisil Kumarawadu, Ph.D., is a Senior Professor in Electrical Engineering at the University of Moratuwa, Sri Lanka, and a distinguished professor at Shanghai University of Electric Power. With expertise in smart energy-efficient systems, systems automation, and AI applications, he has made significant contributions to robotics, intelligent systems, and applied statistics. His leadership extends to his past roles as the Head of the Department of Electrical Engineering and Chairman of the Board of Governors at the Arthur C. Clarke Institute for Modern Technologies. Dr. Kumarawadu’s career includes research, teaching, and mentorship, further enhancing his stature as a leading academic and innovator in electrical engineering. 📚💡🌍

Publication Profile

Scopus

Education:

Dr. Kumarawadu holds a Ph.D. in Robotics and Intelligent Systems from Saga National University, Japan (2003), a Master’s degree in Advanced Systems Control Engineering from the same institution (2000), and a First Class Honours BSc in Electrical Engineering from the University of Moratuwa, Sri Lanka (1996). 🎓📘

Experience:

Dr. Kumarawadu has over two decades of experience in academia, having served as a Senior Professor, Professor, and Associate Professor in Electrical Engineering at the University of Moratuwa. He has held notable positions including the Exetel Endowed Professor in Artificial Intelligence and Postdoctoral Research Fellow at the National Central University, Taiwan. He has delivered keynote speeches at major international conferences and has contributed to several research projects in automation, energy systems, and AI. 🏫🌍📈

Research Interests:

Dr. Kumarawadu’s research interests include smart energy-efficient systems, systems automation and control, AI applications, and applied statistics. He is particularly focused on innovations in robotics, intelligent transportation systems, and sustainable energy solutions, contributing to various cutting-edge advancements in these fields. ⚡🤖🔬

Awards:

Dr. Kumarawadu has received numerous prestigious awards, including the Sri Lanka Education Leadership Award (2019), the National Research Council Merit Award for Scientific Publications (2010), and the Presidential Award for Scientific Research Publications (2007, 2008). He has also been honored as an Overseas Distinguished Professor by Shanghai University of Electric Power and recognized in the Marquis Who’s Who in the World (25th Edition). 🏆🥇🎖️

Publications:

“NILM for Commercial Buildings: Deep Neural Networks Tackling Non-Linear and Multi-Phase Loads,” Energies (Section F: Electrical Engineering), Vol. 17, Issue 15, August 2024.

“A Biphasic Machine Learning Approach for Detecting Electricity Theft Cyberattacks in Smart Grids,” IEEE Trans. Smart Grids (under review).
Link to publication

“Dijkstra Method Based Zone Temperature Management Strategy for Optimal Energy Saving with Guaranteed Thermal Comfort,” The International Journal of Building Science and its Applications (under review).
Link to publication

“Review on Li-Ion Battery Parameter Extraction Methods,” IEEE Access, Vol. 11, 2023.
Link to publication

“Deep Learning-based Non-Intrusive Load Monitoring for a Three-Phase System,” IEEE Access, Vol. 11, 2023.
Link to publication