Maryam Sadeghi | Smart Cities and Architecture | Best Researcher Award

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Mrs. Maryam Sadeghi | Smart Cities and Architecture | Best Researcher Award

Full-time Faculty Member at Islamic Azad University, Iran.

Maryam Sadeghi is an accomplished researcher and faculty member in Electrical Engineering, specializing in smart grids, distributed control, and intelligent energy systems. She has served as a full-time instructor at the Islamic Azad University, Islamshahr Branch, where she has also chaired the Power Engineering Department. Over the years, she has successfully combined teaching, supervision, and leadership with impactful research contributions. As a PhD candidate at the Iran University of Science and Technology, her doctoral work has advanced the field of power systems with an emphasis on adaptive and intelligent control. Beyond academia, she has actively collaborated with national research and industrial centers, particularly in areas such as SCADA applications, FPGA development, and distributed automation. Her career demonstrates a consistent focus on renewable energy integration, intelligent universal transformers, and advanced automation, positioning her as a thought leader in the evolving landscape of modern electrical engineering.

Professional Profile

Google Scholar

Education

Maryam Sadeghi’s educational background reflects a strong and progressive journey through electrical engineering disciplines. She earned her B.Sc. in Electrical Engineering with a focus on Electronics from the Islamic Azad University, Tehran Central Branch. She further specialized in Control Systems at the M.Sc. level from Islamic Azad University, Tehran South Branch, where she explored adaptive control methodologies. To expand her expertise in the energy sector, she pursued doctoral studies in Electrical Engineering with a specialization in Power Systems at the Iran University of Science and Technology. Her PhD research, with defense approved, focuses on advanced power system automation and intelligent control strategies, including adaptive neuro-fuzzy inference systems and multi-agent approaches for smart grids. Through this academic journey, she has built deep expertise in intelligent systems, renewable integration, and distributed energy automation, forming the backbone of her subsequent teaching, research, and industry collaborations in both traditional and emerging power engineering domains.

Experience 

Maryam Sadeghi has built a multifaceted career blending academia, research, and industry collaboration.  She has been a full-time faculty member at the Islamic Azad University, Islamshahr Branch, teaching undergraduate and graduate courses in power systems and control. As Head of the Power Engineering Department for four years, she led curriculum development, faculty coordination, and student mentorship. Her industry-linked research experience includes a decade as Senior Researcher at Novin Ray Control Co., where she worked on solar energy monitoring, SCADA systems, and energy management integration. She has also contributed to telecommunication research through FPGA-based SDH system design, and to control systems development in distributed automation protocols, particularly IEC 61499. These roles reflect her ability to connect theoretical knowledge with practical applications. Her experience across teaching, applied research, and leadership showcases her as a versatile expert committed to advancing both education and innovation in intelligent energy systems.

Research Focus

Maryam Sadeghi’s research is centered on intelligent power systems, with a focus on adaptive control, fuzzy logic, and distributed automation for modern grids. Her work on Intelligent Universal Transformers (IUTs) has introduced innovative control methodologies using fuzzy logic, artificial neural networks, and genetic algorithms to optimize distribution automation. She has also contributed to decentralized multi-agent coordination frameworks for smart distribution restoration, enabling resilience and flexibility in power networks. Her studies in renewable energy integration—particularly inverter-based distributed generation and wind turbine inverters—highlight her commitment to sustainable energy solutions. Additionally, she has advanced methodologies in GPS-based time synchronization and IEC 61499-based distributed control systems. By combining advanced algorithms with real-world applications such as SCADA and EMS, she bridges the gap between theory and practice. Her research trajectory demonstrates a consistent pursuit of scalable, adaptive, and intelligent solutions for next-generation power grids within the context of smart cities and sustainable development.

Awards and Honors

Maryam Sadeghi has received recognition for her academic and research contributions at both institutional and national levels. She has been nominated for the ARCH Best Researcher Award, reflecting her impactful body of work in power systems and control. Her multiple ISI-indexed publications in smart grids, intelligent automation, and renewable energy integration demonstrate her influence in advancing knowledge in her field. As a contributor to national research centers in Iran, she has played a significant role in developing and implementing control solutions aligned with national energy and telecommunication priorities. Her leadership as Head of the Power Engineering Department also underscores her recognition as an academic mentor and innovator. The combination of research excellence, teaching distinction, and industrial collaboration has positioned her as a respected figure within the engineering community. These honors highlight her dedication to advancing intelligent energy solutions and promoting the integration of innovative methodologies into modern power systems.

Publication Top Notes

Title: Time Synchronizing Signal by GPS Satellites
Authors: M. Sadeghi, M. Gholami
Summary: This paper simulates GPS-based synchronization in MATLAB to achieve high-precision timing. It highlights GPS as a reliable solution for communications and distributed automation systems.

Title: Fuzzy Logic Approach in Controlling the Grid Interactive Inverters of Wind Turbines
Authors: M. Sadeghi, M. Gholami
Summary: The study applies fuzzy logic to enhance grid-connected wind turbine inverter performance. Results show improved stability and efficiency under varying wind conditions.

Title: Advanced Control Methodology for Intelligent Universal Transformers Based on Fuzzy Logic Controllers
Authors: M. Sadeghi, M. Gholami
Summary: The authors propose fuzzy logic controllers for Intelligent Universal Transformers (IUTs). The approach improves adaptability and response in advanced distribution automation.

Title: A Novel Distribution Automation Involving Intelligent Electronic Devices as IUT
Authors: M. Sadeghi, M. Gholami
Summary: This paper presents IUTs as intelligent devices for distribution automation. It demonstrates improved grid reliability and fault management.

Title: Fully Decentralized Multi-Agent Coordination Scheme in Smart Distribution Restoration: Multilevel Consensus
Authors: M. Sadeghi, M. Kalantar
Summary: The research introduces a decentralized multi-agent consensus method for smart distribution restoration. It enhances system resilience and scalability without central control.

Title: Developing Adaptive Neuro-Fuzzy Inference System for Controlling the Intelligent Universal Transformers in ADA
Authors: M. Sadeghi, M. Gholami
Summary: An ANFIS-based controller is developed for IUTs to improve adaptability and precision. The hybrid method outperforms conventional control strategies.

Title: Genetic Algorithm Optimization Methodology for PWM Inverters of Intelligent Universal Transformer for the Advanced Distribution Automation of Future
Authors: M. Sadeghi, M. Gholami
Summary: The study uses genetic algorithms to optimize PWM inverters in IUTs. It reduces harmonic distortion and improves inverter efficiency.

Title: Optimized Control Strategy to Adjust the Intelligent Universal Transformer for Integrating Distributed Resources to Grid
Authors: M. Sadeghi, M. Gholami
Summary: This work introduces an optimized control strategy for IUTs to integrate distributed energy resources. It ensures stable and flexible grid operations.

Conclusion

Overall, Maryam Sadeghi is a strong candidate for the Best Researcher Award. Her research reflects both depth and breadth in intelligent power systems, with practical applications that align with the future of energy distribution and smart grid technologies. With her combination of academic leadership, teaching excellence, and impactful research, she demonstrates qualities that merit recognition. By expanding her international reach and enhancing visibility through broader collaborations and higher-impact publications, she can further solidify her position as a leading researcher in her domain.

Yao Lu | Energy-Efficient Architecture | Best Researcher Award

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Assoc. Prof. Dr. Yao Lu | Energy-Efficient Architecture | Best Researcher Award

Associate Reseacher at Beijing Institute of Nanoenergy and Nanosystems, China

Dr. Yao Lu is an accomplished researcher specializing in smart batteries, lithium-ion batteries, and flexible sensors. He earned his Ph.D. from the University of Science and Technology Beijing, where he trained in advanced materials and physics at the Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science. He later joined Tsinghua University as a research fellow at the State Key Laboratory of Automotive Safety and Energy, where he advanced research on energy storage and battery safety. Currently, Dr. Lu serves as an Associate Researcher at the Beijing Institute of Nanoenergy and Nanosystems, Chinese Academy of Sciences. His research emphasizes developing safe, long-life, and energy-efficient battery systems by integrating flexible sensor technologies. With over 25 peer-reviewed publications in leading journals, he has made impactful contributions to both academic science and practical energy applications. Dr. Lu is recognized as a promising researcher shaping the future of sustainable energy storage.

Professional Profile

ORCID

Education

Dr. Yao Lu completed his doctoral studies at the University of Science and Technology Beijing (USTB), where he conducted research at the Beijing Key Laboratory for Magneto-Photoelectrical Composite and Interface Science. His Ph.D. work focused on advanced physics, nanomaterials, and energy systems, laying the foundation for his later work in smart batteries and flexible sensors. At USTB, he gained expertise in electrochemical energy storage mechanisms and safety analysis of high-performance batteries. Following his doctoral training, Dr. Lu pursued additional research opportunities at Tsinghua University, one of China’s most prestigious institutions, where he worked on automotive safety and energy technologies. These academic experiences provided him with a strong interdisciplinary background combining physics, materials science, electrochemistry, and engineering. This broad training equipped him to tackle the pressing challenges in next-generation energy storage technologies, particularly in developing safe, intelligent, and energy-efficient battery systems suitable for electric vehicles and renewable energy applications.

Research Focus 

Dr. Yao Lu’s research focuses on the intersection of energy storage technology, sensor integration, and sustainability. His primary work explores smart lithium-ion batteries enhanced with flexible and implantable sensors that improve safety, performance, and life cycle management. He investigates critical challenges in battery technology, including thermal runaway mechanisms, lithium dendrite suppression, and rapid charging solutions. By combining materials engineering, electrochemical analysis, and sensor fusion techniques, his work aims to create next-generation batteries that are both safe and efficient. Additionally, Dr. Lu contributes to research on zinc-ion batteries and sodium-ion batteries, offering sustainable alternatives to traditional lithium-ion systems. His studies also incorporate AI-enabled battery management systems, providing intelligent monitoring and predictive maintenance capabilities for electric vehicles and large-scale energy storage. Overall, his research represents a forward-looking approach to clean energy innovation, addressing global needs for safer, more reliable, and environmentally responsible power storage solutions.

Publication Top Notes

Title: Zinc-ion batteries: pioneering the future of sustainable energy storage through advanced materials and mechanisms
Authors: Zixuan Chen, Liang Zhang, Tianyu Yu, Huancheng Yang, Yao Lu, Xiaodan Wang, Rui Li, Zonglun Ye, Yue Wang, Pengwei Li et al.
Summary: This article explores zinc-ion batteries as sustainable alternatives to lithium-ion systems. It provides mechanistic insights and highlights material strategies for performance enhancement, opening pathways for environmentally friendly storage solutions.

Title: Manipulation of lithium dendrites based on electric field relaxation enabling safe and long-life lithium-ion batteries
Authors: Xuebing Han, Shuoyuan Mao, Yu Wang, Yao Lu, Depeng Wang, Yukun Sun, Yuejiu Zheng, Xuning Feng, Languang Lu, Jianfeng Hua et al.
Summary: This study addresses lithium dendrite formation, a critical safety issue. The team demonstrated how electric field relaxation strategies can suppress dendrites, prolonging battery life and improving reliability.

Title: AI enabled fast charging of lithium-ion batteries of electric vehicles during their life cycle: review, challenges and perspectives
Authors: Daoming Sun, Dongxu Guo, Yufang Lu, Jiali Chen, Yao Lu, Xuebing Han, Xuning Feng, Languang Lu, Hewu Wang, Minggao Ouyang
Summary: A comprehensive review highlighting AI-driven methods for safe fast charging. The paper identifies challenges and future directions for integrating AI with EV battery management.

Title: Early warning for thermal runaway in lithium-ion batteries during various charging rates: Insights from expansion force analysis
Authors: Kuijie Li, Chen Li, Xuebing Han, Xin Gao, Yao Lu, Depeng Wang, Weixiong Wu, Yuan-cheng Cao, et al.
Summary: This work introduces expansion force analysis as a diagnostic method for predicting thermal runaway, contributing to improved safety monitoring in Li-ion batteries.

Title: In situ evaluation and manipulation of lithium plating morphology enabling safe and long-life lithium-ion batteries
Authors: Shuoyuan Mao, Yu Wang, Yao Lu, Xuebing Han, Yuejiu Zheng, Xuning Feng, Xinqi Ren, Languang Lu, Minggao Ouyang
Summary: The study reports advanced in situ techniques to monitor and control lithium plating, enhancing battery safety and durability.

Title: Smart batteries enabled by implanted flexible sensors
Authors: Yao Lu, Xiaodan Wang, Shuoyuan Mao, Depeng Wang, Daoming Sun, Yukun Sun, Anyu Su, Chenzi Zhao, Xuebing Han, Kuijie Li et al.
Summary: This article highlights how flexible sensors implanted within batteries can revolutionize energy storage by enabling real-time state monitoring and improved safety performance.

Conclusion

Dr. Yao Lu is an outstanding candidate for a Best Researcher Award. His innovative work on smart, safe, and sustainable battery technologies positions him at the forefront of energy materials research. With strong publication achievements, impactful collaborations, and recognition through competitive grants, he demonstrates the qualities of a researcher whose contributions will continue to shape the future of energy storage and flexible sensing technologies.