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.

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. 🚀

Mr. Federico Briatore | Industry 4.0 | Best Researcher Award

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Mr. Federico Briatore | Industry 4.0 | Best Researcher Award

University of Genoa, Italy

Federico Briatore is a dynamic researcher and consultant from Italy, specializing in Industry 4.0, Artificial Intelligence, and Healthcare. With a strong background in engineering and business administration, he has worked on optimizing industrial processes, implementing AI-driven solutions, and advancing digital transformation in various sectors. His expertise spans economic analysis, digital transformation, predictive modeling, and automation. Federico has also contributed significantly to academia with numerous research publications in top-tier journals and conferences.

Publication Profile

🎓 Education

Federico holds a Ph.D. in Engineering of Models, Machines, and Systems for Energy, Environment, and Transportation (expected in 2025). He has also earned a Master’s Degree (Level II) in Artificial Intelligence and Blockchain, an MBA (Level II) with honors, and a Master’s Degree in Management Engineering. Additionally, he is a certified engineer in both the Industrial and Information sectors. His educational foundation is further strengthened by a Bachelor’s Degree in Industrial and Management Engineering and a High School A-level diploma in Administration, Finance, and Marketing.

💼 Experience

Federico has extensive experience across multiple industries, including consultancy roles at Regione Liguria, Covim SPA, and OM3 Engineering SRL, where he optimized production processes and digital transformation strategies. His expertise in AI was further honed at Metakol S.r.l., where he trained AI models for insurance fraud detection and maritime forecasting. He has also served as a high school professor, teaching Mathematics, Computer Science, and Physics. His work spans market analysis, financial statement analysis, process optimization, and AI-driven solutions for industrial and healthcare applications.

🏆 Awards and Honors

Federico has been recognized for his academic excellence, securing 110/110 in his Master’s degrees and an MBA with honors (110 con lode/110). His innovative projects in Industry 4.0 and Healthcare AI have been acknowledged through publications in prestigious journals and conferences. His engineering and technological solutions have contributed to advancements in sustainable supply chains, hospital management, and industrial automation.

🔬 Research Focus

Federico’s research interests revolve around Industry 4.0, Artificial Intelligence, and Healthcare Systems. His work integrates IoT, Cyber-Physical Systems, and AI-driven predictive modeling to optimize industrial and medical processes. He has conducted bibliometric analyses on sustainable supply chains, developed AI models for maritime forecasting, and worked on Engineering 4.0 applications to combat hospital infections and enhance bed management systems.

🔎 Conclusion

Federico Briatore is a multidisciplinary expert in Industry 4.0, AI, and digital transformation, contributing both academically and professionally to technological advancements in healthcare and industrial sectors. His diverse research, consultancy, and teaching experiences make him a key figure in modern engineering and business innovations. 🚀

📖 Publications

Exploring Industry 4.0’s Role in Sustainable Supply Chains: Perspectives from a Bibliometric Review (2025) – Logistics

Advanced 4.0 Bed Management System, embedded with IoT, Digital Twins, and Cyber-Physical System (2024) – TechRxiv

Personal Protective Equipment Management and Maintenance: An Innovative Project Conducted in a Major Italian Manufacturing Company (2023) – WSEAS Transactions on Systems

A Literature Review on Applied AI to Public Administration: Insights from Recent Research and Real-Life Examples (2023) – Book Chapter

An Application of Engineering 4.0 to Hospitalized Patients (2023) – SysInt 2022 Conference

Fighting Hospital Infections with Engineering 4.0 (2023) – SysInt 2022 Conference

Artificial Intelligence for Supporting Forecasting in the Maritime Sector (2022) – Summer School Francesco Turco Proceedings

Engineering Solutions 4.0 in the Fight Against the Spread of COVID-19 (2022) – Summer School Francesco Turco Proceedings

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