Prof. Dr. HyunJe Oh | Cyber-Physical Systems | Best Researcher Award

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Prof. Dr. HyunJe Oh | Cyber-Physical Systems | Best Researcher Award

Prof. Dr HyunJe Oh | Korea Institute of Construction Technology | South Korea

Prof. Dr. Hyun Je Oh is a highly respected expert in civil, environmental, and water engineering, known for his extensive contributions as a Senior Research Fellow at the Korea Institute of Construction Technology and as a Professor at the University of Science and Technology. With advanced academic training culminating in a Doctor of Philosophy degree in Civil and Environmental Engineering, he has led 112 national research and development projects completed by 2025, contributing significantly to advancements in water treatment, environmental protection, and engineering innovation. His professional leadership includes long-term service in the Clean Water Forum Committee of the National Assembly, presidency of the Korea Society on Water and Wastewater from 2015 to 2017, and chairing the Seoul Metropolitan Government Tap Water Evaluation Committee from 2010 to 2012. Prof. Dr. Oh’s scholarly achievements include 51 published documents, 69 domestic and international research papers, and 421 academic presentations. His work has received 783 citations from 729 referencing documents, supported by a citation index score of 13. He also maintains a strong record in industrial innovation, with 96 patent applications and registrations, 61 officially granted patents, and 17 technologies successfully transferred to industry, demonstrating substantial impact on clean water systems and sustainable engineering practices.

Profile: Scopus

Featured Publications

Oh, H. J. (2026). Optimal data pooling from multiple waterbodies to improve machine-learning predictions of cyanobacterial blooms. Journal of Contaminant Hydrology.

Oh, H. J. (2026). Evaluating circulation-type membrane capacitive deionization as a dual-function system for ion removal and enrichment. Desalination.

Oh, H. J. (2025). Enhanced desalination performance of pilot-scale membrane capacitive deionization system with circulation process. Desalination.

Oh, H. J. (2024). Performance optimization of a pilot-scale membrane capacitive deionization system operating with circulation process. Separation and Purification Technology.

Oh, H. J. (2023). Optimizing operational conditions of pilot-scale membrane capacitive deionization system. Sustainability.

Dr. S. Thirunavukkarasu | AI in Engineering | Best Researcher Award

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Dr. S. Thirunavukkarasu | AI in Engineering | Best Researcher Award

Dr. S. Thirunavukkarasu | Indira Gandhi Centre for Atomic Research | India

Dr. S. Thirunavukkarasu research focuses on quantitative nondestructive evaluation (NDE), finite element (FE) modeling, digital signal and image processing, and the development of innovative sensors and instrumentation for advanced inspection applications. His work emphasizes multi-parametric linear and nonlinear regression, radial basis function (RBF), and multidimensional RBF neural networks for accurate flaw sizing in eddy current testing. He has contributed to FE modeling of electromagnetic NDE phenomena, including the optimization of remote field eddy current probe parameters for ferromagnetic steam generator tube inspections and modeling of magnetic flux leakage considering nonlinear magnetic permeability. His studies extend to the simulation of pulsed and sweep frequency eddy current methods to improve detection efficiency. Additionally, his research in wavelet transform–based digital signal processing enhances the interpretation of eddy current signals from complex regions such as bends and support plate intersections. He has also advanced in-house development of remote field eddy current techniques for the inspection of modified 9Cr-1Mo steel steam generator tubes. His computational expertise includes MATLAB, Python, and LabVIEW, alongside specialized software such as COMSOL, FEMM, and CIVA for modeling and simulation in electromagnetic and NDE applications.

Profile: Orcid

Featured Publications

Arun, A. D., Rajiniganth, M. P., Chandra, S., & Thirunavukkarasu, S. (2025). A numerical model of parallel disc capacitor probe used in nondestructive dielectric permittivity evaluation by algebraic topological method. International Journal of Applied Electromagnetics and Mechanics, 2025-09.

Sharatchandra Singh, W., Haneef, T. K., Thirunavukkarasu, S., & Kumar, A. (2025). In-situ measurement of tensile deformation-induced magnetic fields in high strength low alloy steels using GMR based metal magnetic memory technique. International Journal of Applied Electromagnetics and Mechanics, 2025-09-10.

Arun, A. D., Chandra, S., Thirunavukkarasu, S., Rajiniganth, M. P., Malathi, N., & Sivaramakrishna, M. (2025). A novel algebraic topological method-based approach for evaluating stored electrostatic energy and 3D Maxwellian capacitance. Journal of Electrostatics, 2025-06.

Thirunavukkarasu, S., Kumar, A., Martin, J. P., Harini, T., Reddy, S., Emil, S., & Balu, C. (2025). Automated detection of defects in eddy current inspection data using machine learning methods. International Journal of Applied Electromagnetics and Mechanics, 2025-06-03.

Balakrishnan, S., Das, C. R., Thirunavukkarasu, S., & Kumar, A. (2025). In-situ hardness evaluation of hard-faced coatings through eddy current NDE. International Journal of Applied Electromagnetics and Mechanics, 2025-05-23.

Vijayachandrika, T., Arjun, V., Thirunavukkarasu, S., & Kumar, A. (2025). Design, fabrication, and characterization of staggered array radial coil RFEC probe for small diameter ferritic steel tube. IEEE Sensors Journal, 2025-05-01.

Dr. Xiuyun Zhang | Control Systems Engineering | Best Researcher Award

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Dr. Xiuyun Zhang | Control Systems Engineering | Best Researcher Award

Dr. Xiuyun Zhang | Tianjin University of Technology and Education | China

Dr. Xiuyun Zhang is a lecturer and researcher specializing in motor systems and their control, with a particular emphasis on multi-motor collaborative control. Her teaching covers theoretical foundations such as circuit principles and automatic control principles, while her research explores torque coordination in large-load drives, speed coordination in industrial applications, and position coordination and contour control in high-precision CNC machining. She has published over 20 SCI/EI indexed papers and more than 10 journal publications, with a record of 972 citations from 914 documents, 94 published works, and an h-index of 16. Her innovative contributions are reflected in 16 granted or filed patents, including invention and utility model patents. As a project leader, she has directed research supported by the Tianjin Natural Science Foundation Youth Project, the Tianjin Higher Education Science and Technology Development Fund, an invention patent conversion initiative, and several horizontal projects, while also contributing as a main researcher to a National Natural Science Foundation general project. With more than five completed or ongoing research projects, her work focuses on developing predictive and interactive control strategies that use speed and current as internal system variables, aiming to improve collaborative control accuracy and dynamic response in advanced motor applications.

Profile: Scopus | Google Scholar | Orcid

Featured Publications

  • Zhang, R., Zong, Q., Zhang, X., Dou, L., & Tian, B. (2022). Game of drones: Multi-UAV pursuit-evasion game with online motion planning by deep reinforcement learning. IEEE Transactions on Neural Networks and Learning Systems, 34(10), 7900–7909.

  • Wang, D., Zong, Q., Tian, B., Shao, S., Zhang, X., & Zhao, X. (2018). Neural network disturbance observer-based distributed finite-time formation tracking control for multiple unmanned helicopters. ISA Transactions, 73, 208–226.

  • Dou, L., Cai, S., Zhang, X., Su, X., & Zhang, R. (2022). Event-triggered-based adaptive dynamic programming for distributed formation control of multi-UAV. Journal of the Franklin Institute, 359(8), 3671–3691.

  • Liu, D., Dou, L., Zhang, R., Zhang, X., & Zong, Q. (2022). Multi-agent reinforcement learning-based coordinated dynamic task allocation for heterogeneous UAVs. IEEE Transactions on Vehicular Technology, 72(4), 4372–4383.

  • Ye, L., Zong, Q., Tian, B., Zhang, X., & Wang, F. (2017). Control-oriented modeling and adaptive backstepping control for a nonminimum phase hypersonic vehicle. ISA Transactions, 70, 161–172.

  • Zhang, X., Zong, Q., Dou, L., Tian, B., & Liu, W. (2020). Finite-time attitude maneuvering and vibration suppression of flexible spacecraft. Journal of the Franklin Institute, 357(16), 11604–11628.

  • Zhang, X., Zong, Q., Dou, L., Tian, B., & Liu, W. (2020). Improved finite-time command filtered backstepping fault-tolerant control for flexible hypersonic vehicle. Journal of the Franklin Institute, 357(13), 8543–8565.

 

 

Dr. Mingwei Zhao | Electrical Engineering | Excellence in Research Award

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Dr. Mingwei Zhao | Electrical Engineering | Excellence in Research Award

Dr. Mingwei Zhao , Jiangsu Normal University & Shanghai University , China.

Dr. Mingwei Zhao 🎓, born in Shandong, China 🇨🇳, is a dedicated researcher and educator in the field of electrical engineering ⚡. He currently serves as a Lecturer at Jiangsu Normal University 🏫, specializing in power electronics and robotic systems 🤖. With a strong foundation in mechanical and electrical integration 🔧, he pursued advanced studies in power drive systems and control science 🎛️. His ongoing research is focused on innovative power electronic drive technologies and intelligent robotics 💡. Dr. Zhao’s work contributes significantly to automation and energy efficiency solutions in modern engineering 🌐.

Professional Profile

Scopus

Education & Experience

  • 🎓 B.S. in Mechanical and Electrical Integration, Nanjing University of Science and Technology, 2004

  • 🎓 M.S. in Power Electronics and Power Drive, Nanjing University of Aeronautics and Astronautics, 2012

  • 🎓 Ph.D. (in progress) in Control Science and Engineering, Shanghai University, since 2016

  • 👨‍🏫 Lecturer, School of Electrical Engineering and Automation, Jiangsu Normal University

Summary Suitability

Dr. Mingwei Zhao is a highly dedicated and innovative researcher, making him a strong candidate for the Excellence in Researcher Award. With a solid academic foundation and over a decade of hands-on experience, Dr. Zhao has significantly advanced the fields of power electronics drive technologies and robotic systems through both applied research and academic leadership.

Professional Development

Dr. Zhao has continually expanded his expertise through rigorous academic pursuits and hands-on teaching experience 👨‍🔬. Currently undertaking his Ph.D. at Shanghai University 🎓, he stays at the forefront of technological innovation by integrating control systems and robotics into his curriculum 🤖📘. His involvement in both academic and applied research ensures that his contributions are both theoretically sound and practically relevant 🛠️. As a Lecturer, he mentors students and fosters a dynamic learning environment 🎤💡. His professional development reflects a balanced focus on research, teaching, and practical implementation in modern automation systems 🚀.

Research Focus

Dr. Zhao’s research is centered in the Electrical and Automation Engineering category ⚙️, with a specialized emphasis on power electronic drive systems ⚡ and robotic control integration 🤖. He explores the design and control of energy-efficient power systems, automation technology, and intelligent robotic operations 🔋🔍. His current studies contribute to advancing smart drive technologies that are vital for automation and Industry 4.0 initiatives 🏭💡. By leveraging multidisciplinary principles, he aims to develop sustainable and intelligent engineering systems that enhance the performance and adaptability of electrical devices 🌱🧠.

Publication Top Notes

  • Title:
    An Open-Circuit Fault Diagnosis for Three-Phase PWM Rectifier Without Grid Voltage Sensor Based on Phase Angle Partition

  • Authors:
    Mingwei Zhao, et al.

  • Journal:
    IEEE Transactions on Circuits and Systems I: Regular Papers

  • Publisher:
    IEEE (Institute of Electrical and Electronics Engineers)

  • Year:
    2024

  • Citations:
    4 (as of the latest count)

  • Summary:
    This article presents a fault diagnosis method for three-phase PWM rectifiers that eliminates the need for a grid voltage sensor. It uses phase angle partitioning to detect open-circuit faults efficiently, enhancing system reliability.

Conclusion

Dr. Zhao’s pioneering efforts and sustained contributions to power electronics and robotics make him a worthy nominee for the Excellence in Researcher Award. His blend of theoretical expertise, practical engineering solutions, and educational leadership continues to push the boundaries of automation and intelligent systems, benefiting both academia and industry.