Dr. Yuxiang Leng | Electrical engineering | Best Researcher Award

Dr. Yuxiang Leng | Electrical engineering | Best Researcher Award

Ph.D, Chongqing University, China

Yuxiang Leng is an emerging researcher in the field of 3D laser point cloud technology and power transmission systems. He is currently pursuing his Ph.D. at the State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, China. With a strong academic background and an innovative mindset, Leng has actively contributed to the advancement of computer vision applications in power systems. He has published eight academic papers and presented his work at high-level international conferences, gaining recognition in both academia and industry for his contributions to smart grid technologies and engineering digitalization.

Publication Profile

Scopus

🎓 Education Background:

Yuxiang Leng earned his B.Sc. degree from Jiangsu University of Science and Technology in 2019 and his M.S. degree from Wenzhou University in 2022. He is currently a Ph.D. candidate at Chongqing University, focusing on advanced research in the digital management of power substations using 3D vision and laser scanning methods. His educational path reflects a consistent pursuit of excellence in engineering and technology.

💼 Professional Experience:

Though still in the early stages of his research career, Yuxiang has shown remarkable productivity. He has been actively involved in eight research projects and has taken a lead role in multiple academic studies. His technical work centers around developing high-precision measurement techniques and improving data accuracy in laser-based 3D reconstruction. While he has not yet been involved in consultancy or editorial positions, his practical approach and novel methodologies have already earned him significant attention in academic forums.

🏅 Awards and Honors:

While specific awards are not listed, Yuxiang’s recognition as a leading contributor to peer-reviewed SCI/EI journals, including being the first author in three high-impact publications, underlines his academic excellence. Additionally, his oral presentations at top-tier international conferences have positioned him as a rising talent in power equipment digitalization. His selection as an IEEE Student Member further reflects his commitment to research and innovation.

🔬 Research Focus:

Yuxiang’s research lies at the intersection of 3D computer vision, laser point cloud data analysis, and power transmission and transformation systems. His most notable contribution involves a dynamic compensation method that significantly reduces vibration-induced errors in 3D point cloud data, enhancing segmentation and reconstruction precision by over 70%. His work not only advances digital twin modeling but also supports smart maintenance, monitoring, and intelligent management of electrical substations.

🔚 Conclusion:

Yuxiang Leng stands out as a dynamic and promising young researcher whose innovative solutions are driving the future of power system digitalization. With a strong publication record, hands-on project experience, and a clear research vision, he is a fitting candidate for the Best Researcher Award. His blend of academic rigor and practical innovation ensures a meaningful impact in the realm of intelligent power grid technology.

📚 Top Publications of Yuxiang Leng

  1. Dynamic compensation approach for mitigating vibration interference in 3D point cloud data of electrical equipment
    Published: 2025
    Journal: Advanced Engineering Informatics
    Cited by: 3 articles

  2. Intelligent Early Warning System for Power Operation Safety Based on Laser Point Cloud Sensing
    Published: 2024
    Conference Paper: International Conference on Smart Energy Systems
    Cited by: 2 articles

  3. LoRaWAN Network Downlink Routing Control Strategy Based on the SDN Framework and Improved ARIMA Model
    Published: 2023
    Journal: Journal of Communications and Networks
    Cited by: 1 article

  4. Contactless Voltage Measurement Considering Spatially Dependent Voltage Compensation
    Published: 2023
    Conference Proceedings: IEEE Power & Energy Society Meeting
    Cited by: 0 articles

 

Jian Sun | Smart Grid Control | Best Researcher Award

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

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