Hyeonmin Jeon | Electrical Engineering | Best Research Article Award

Published on by Award and Honors

Best Research Article Award

Hyeonmin Jeon
Korea Maritime and Ocean University

Hyeonmin Jeon
Affiliation Korea Maritime and Ocean University
Country South Korea
Scopus ID 57190843421
Documents 29
Citations 349
h-index 10
Subject Area Electrical Engineering
Event Award and Honors
ORCID
0000-0001-8303-1248

Hyeonmin Jeon is affiliated with Korea Maritime and Ocean University in South Korea and has contributed to the field of Electrical Engineering through scholarly research focused on advanced engineering systems, electronic technologies, and applied scientific innovation. The researcher has established a measurable academic impact through indexed publications, citation performance, and interdisciplinary collaboration within engineering-related domains.[1] The academic profile demonstrates sustained engagement in research activities relevant to emerging electrical engineering technologies and scientific dissemination through internationally indexed publications.[2]

Abstract

This article presents an academic overview of Hyeonmin Jeon and the researcher’s scholarly contributions within the discipline of Electrical Engineering. The profile reflects measurable scientific activity through Scopus-indexed publications, citation metrics, and research dissemination across engineering-oriented studies. The evaluation highlights publication productivity, citation influence, and participation in technological research initiatives relevant to contemporary engineering systems.[1] The article further examines the researcher’s suitability for recognition under the Best Research Article Award category associated with the Award and Honors platform.

Keywords

Electrical Engineering, Engineering Research, Research Excellence Award, Scientific Publications, Research Impact, Scopus Indexing, Academic Recognition, Technology Innovation, Renewable Energy Systems, Artificial Intelligence in Engineering, Smart Grid Technology, Sustainable Engineering, Applied Electrical Sciences, Scientific Impact

Introduction

Electrical Engineering remains one of the most influential scientific disciplines supporting technological development, industrial automation, communication systems, and computational innovation. Researchers in this field contribute to the advancement of modern engineering applications through experimental investigations, analytical methodologies, and interdisciplinary collaboration.

Hyeonmin Jeon has developed an academic research profile characterized by peer-reviewed publications and measurable citation indicators. Affiliated with Korea Maritime and Ocean University, the researcher’s work contributes to engineering-oriented scientific literature and demonstrates active participation in contemporary research environments.[1] The available bibliometric indicators indicate scholarly consistency and engagement with internationally indexed research platforms.[2]

Research Profile

The academic profile of Hyeonmin Jeon demonstrates sustained scholarly productivity within the domain of Electrical Engineering. The researcher possesses a Scopus Author ID of 57190843421 and has produced 29 indexed documents with 349 citations and an h-index of 10.[1] These bibliometric indicators suggest consistent academic engagement and research dissemination across recognized scientific publication channels.

Research conducted within engineering disciplines frequently involves analytical modeling, system optimization, electronic design methodologies, and technology-oriented experimentation. The researcher’s publication record indicates participation in scientific discussions relevant to engineering advancement and interdisciplinary problem-solving approaches.

Research Contributions

Hyeonmin Jeon has contributed to the dissemination of engineering knowledge through indexed scientific publications addressing themes associated with Electrical Engineering and applied technological systems. The research contributions reflect participation in studies emphasizing engineering innovation, technical analysis, and scientific methodology.

  • Development and analysis of engineering-oriented research methodologies.
  • Contribution to peer-reviewed scientific literature within Electrical Engineering.
  • Participation in interdisciplinary engineering and technological investigations.
  • Support for academic knowledge dissemination through indexed publications and citations.

The cumulative citation record associated with the researcher’s publications suggests that the work has achieved visibility within academic and technical research communities.[1] Citation-based impact indicators remain widely recognized as measures of scholarly influence and research relevance within scientific publishing systems.

Publications

The publication portfolio associated with Hyeonmin Jeon reflects participation in peer-reviewed engineering research and internationally indexed academic dissemination. Indexed publication records contribute to scholarly communication and support the evaluation of scientific influence within engineering disciplines.[1] Representative DOI-linked scientific publication references within engineering and technology-related research environments may include structured digital object identifiers for long-term citation tracking and academic indexing.

Research Impact

Research impact within scientific disciplines is frequently evaluated through citation performance, publication consistency, and academic visibility across recognized indexing platforms. Hyeonmin Jeon’s citation profile indicates measurable scholarly engagement, with 349 citations and an h-index of 10 demonstrating recognized academic interaction with published research outputs.[1]

Engineering research contributes significantly to technological innovation, infrastructure development, computational systems, and industrial modernization. Researchers participating in these areas support broader scientific progress through the dissemination of validated methodologies and peer-reviewed investigations.

Award Suitability

The academic profile of Hyeonmin Jeon demonstrates characteristics commonly associated with scholarly recognition within engineering-related award categories. Publication productivity, citation performance, and participation in internationally indexed research dissemination collectively support consideration for the Best Research Article Award under the Award and Honors initiative.

The researcher’s documented scholarly activity reflects measurable academic engagement and sustained contributions to Electrical Engineering research. The combination of citation metrics, publication consistency, and institutional affiliation indicates a recognized presence within the academic engineering research community.[1]

Conclusion

Hyeonmin Jeon represents an active academic contributor within the field of Electrical Engineering through indexed publications, measurable citation metrics, and engagement in engineering-focused scientific research. The available academic indicators demonstrate scholarly consistency and research visibility within recognized publication systems.[1]

The researcher’s academic profile aligns with the objectives of professional research recognition initiatives emphasizing publication quality, scientific dissemination, and measurable scholarly influence. The profile therefore reflects suitability for consideration within academic distinction and award-oriented evaluation frameworks.

References

  1. Elsevier. (n.d.). Scopus author details: Hyeonmin Jeon, Author ID 57190843421. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57190843421
  2. ORCID. (n.d.). Research profile of Hyeonmin Jeon. ORCID Registry.
    https://orcid.org/0000-0001-8303-1248
  3. Kim, S., & Jeon, H. (2025). Empirical research to design rule-based strategy control with energy consumption minimization strategy of energy management systems in hybrid electric propulsion systems. Journal of Marine Science and Engineering. https://www.mdpi.com/2077-1312/13/9/1695
  4. Jung, J., Jeon, H., Kim, H., & Kim, S. (2025). A novel approach for the systematic evaluation and optimization of performance and emissions in hybrid electric propulsion systems. Journal of Marine Science and Engineering, 13(2),328. https://www.mdpi.com/2077-1312/13/2/328
  5. Roh, C., Jeon, H.-m., Kim, S.-w., Kim, J.-s., Song, S.-w., Lee, N.-y., & Kang, S.-c. (2025). A study on equivalent series resistance estimation compensation for DC-link capacitor life diagnosis of propulsion drive in electric propulsion ship. Processes, 13(2), 291.  https://www.mdpi.com/2227-9717/13/2/291

Phuet Prasertcharoensuk | Chemical Engineering | Research Excellance Award

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Assist. Prof. Dr. Phuet Prasertcharoensuk | Chemical Engineering | Research Excellance Award

Lecturer | The University of  Chulalongkorn University | Thailand

Assist. Prof. Dr. Phuet Prasertcharoensuk is an accomplished chemical engineering researcher specializing in sustainable energy technologies, biomass conversion, and hydrogen production. His research emphasizes thermochemical processing, heterogeneous catalysis, and carbon dioxide capture and utilization to support cleaner and more efficient energy systems. With 18 scholarly publications, 299 citations, and an h-index of 10, he has contributed to advancements in biomass gasification, hybrid energy systems, and renewable fuel development. His work also incorporates computational modeling, process integration, and innovative approaches such as cold plasma technologies. Through interdisciplinary research, he aims to improve energy efficiency, reduce environmental impact, and support the transition toward low-carbon and circular energy systems.

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Farshad Shamlu | Engineering | Innovative Research Award

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Mr. Farshad Shamlu | Engineering | Innovative Research Award

Doctoral Student | The University of  Genoa | Italy

Mr. Farshad Shamlu is an emerging researcher in the field of modeling and simulation, focusing on complex systems across logistics, supply chains, and engineering applications. His research combines computational modeling, machine learning, and data analytics to address real-world industrial and technological challenges. He has been involved in the development of simulation-based solutions, including high-level architecture (HLA) frameworks and innovative system designs for advanced operational environments. His work also explores sustainability and optimization in engineering systems, contributing to efficient and intelligent decision-making processes. With a record of 2 publications, 5 citations, and an h-index of 1, his research demonstrates a promising trajectory in simulation science, reflecting both technical depth and interdisciplinary integration in modern engineering practices.

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Rossella Marmo | Architectural engineering | Research Excellence Award

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Dr. Rossella Marmo | Architectural engineering | Research Excellence Award

Researcher | The University of  Naples Federico II | Italy

Dr. Rossella Marmo is a researcher in architectural engineering whose work advances resilient and sustainable built environments through digital innovation and risk-based methodologies. Her research integrates Building Information Modelling (BIM) with performance monitoring, enabling improved facility management and lifecycle decision-making. She has developed frameworks for assessing multi-hazard vulnerability of buildings, particularly focusing on hospital resilience, urban risk, and infrastructure safety. Her contributions include stress-testing models, façade vulnerability assessment, and data-driven approaches to disaster risk reduction. Her research supports safer cities by linking building performance with urban-scale impacts. With 21 publications, 210 citations, and an h-index of 6, her scholarly output reflects a strong commitment to advancing resilient infrastructure and sustainable architectural systems through interdisciplinary approaches.

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Konstantinos Blazakis | Engineering | Research Excellance Award

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Dr. Konstantinos Blazakis | Engineering | Research Excellance Award

Adjunct professor | Hellenic Mediterranean University | Greece

Dr. Konstantinos Blazakis is an electrical and computer engineer and AI researcher specializing in smart energy systems, renewable energy analytics, and advanced machine learning. His work integrates artificial intelligence, quantum machine learning, and power systems, with a strong focus on electricity theft detection, forecasting, and smart grid optimization. He has advanced academic training in electrical and computer engineering, smart grid measurement processing, and applied mathematics and physics, enabling a multidisciplinary approach to energy challenges. His professional background spans university-level teaching, EU-funded renewable energy and photovoltaic research projects, smart grid resilience studies, and contributions to industrial photovoltaic installations and power network design. His research interests include machine learning and deep learning for energy forecasting, smart meter data analytics, quantum neural networks, vehicle-to-grid modeling, and energy market analysis, as well as emerging nanoelectronic devices for next-generation sensing and computing. His work supports the development of resilient, intelligent, and low-carbon energy infrastructures.

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Ehsan Khajavian | Engineering | Research Excellance Award

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Mr. Ehsan Khajavian | Engineering | Research Excellance Award

Research Assistant | Ferdowsi University of Mashhad | Iran

Mr. Ehsan Khajavian is a materials and corrosion engineer with strong academic and industrial expertise in corrosion protection, electrochemical analysis, and surface engineering. He holds advanced training in corrosion and protection of materials and materials and metallurgical engineering, with a focus on electrochemical methods, microstructural engineering, and functional surface fabrication. His experience spans academic laboratory supervision, teaching support, and senior industrial roles in technical engineering, metallurgy, and equipment refurbishment. He has contributed to international journals and industrial R&D projects involving corrosion-resistant coatings, casting systems, surface modification, electrochemical instrumentation, and production-line optimization. His research interests center on corrosion science, electrochemical characterization techniques, functional and superhydrophobic surfaces, nanostructured coatings, friction stir processing, and applied corrosion engineering, integrating laboratory-scale research with real-world industrial challenges to deliver durable and scalable materials solutions.

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Corrosion Protection Strategies for Industrial Equipment Using Electrochemical Techniques

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Zhi Zong | Engineering | Best Researcher Award

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Prof. Dr. Zhi Zong | Engineering | Best Researcher Award

Fuyao University of Science and Technology | China

Professor Zhi Zong is an internationally acclaimed researcher in naval architecture, ocean engineering, computational mechanics, and fluid–structure interaction, widely recognized for his influential contributions to marine hydrodynamics and advanced numerical simulation. With 334 publications, 5,653 citations, and an h-index of 38 (Scopus), his research covers underwater explosion (UNDEX) physics, nonlinear water waves, bubble dynamics, vortex-induced vibration (VIV), unsteady cavitation, water-entry dynamics, and high-fidelity computational fluid mechanics, employing cutting-edge techniques such as SPH, DEM, and data-driven modeling. He has authored over 460 scientific papers, including more than 230 SCI-indexed articles, and has been continuously listed among the Top 2% Scientists globally (2021–2025). His seven authoritative monographs published with Elsevier, Taylor & Francis/CRC, and Science Press span differential quadrature methods, solitary wave theory, computational underwater explosion mechanics, and bubble damage modeling. Professor Zong’s research has significantly advanced understanding of shock loading on marine structures, hydrodynamic impact, cavitating and multiphase flows, ice–structure interactions, ship motion reduction, and complex multi-physics simulations, with many of his highly cited publications regarded as landmark contributions to SPH modeling, multiphase flow analysis, UNDEX damage prediction, and VIV dynamics.

Profiles: Scopus| Google Scholar | ResearchGate

Featured Publications 

• Liu, M. B., Liu, G. R., Lam, K. Y., & Zong, Z. (2003). Smoothed particle hydrodynamics for numerical simulation of underwater explosion. Computational Mechanics, 30(2), 106–118.

• Liu, M. B., Liu, G. R., Zong, Z., & Lam, K. Y. (2003). Computer simulation of high explosive explosion using smoothed particle hydrodynamics methodology. Computers & Fluids, 32(3), 305–322.

• Zong, Z., & Zhang, Y. (2009). Advanced differential quadrature methods. Chapman and Hall/CRC.

• Chen, Z., Zong, Z., Liu, M. B., Zou, L., Li, H. T., & Shu, C. (2015). An SPH model for multiphase flows with complex interfaces and large density differences. Journal of Computational Physics, 283, 169–188.

• Zhang, Y. Y., Wang, C. M., Duan, W. H., Xiang, Y., & Zong, Z. (2009). Assessment of continuum mechanics models in predicting buckling strains of single-walled carbon nanotubes. Nanotechnology, 20(39), 395707.

Hongming Zhang | Engineering | Best Researcher Award

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Assoc. Prof. Dr. Hongming Zhang | Engineering | Best Researcher Award

Academician | Beijing University of Posts and Telecommunications | China

Dr. Hongming Zhang is an accomplished Associate Professor at the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China. He earned his Ph.D. in Electrical and Electronic Engineering from the University of Southampton under the supervision of Prof. Lajos Hanzo and Prof. Lie-Liang Yang, following his M.Sc. from Southampton, B.Eng. with Honors from City, University of London, and B.Eng. in Information Engineering from Nanjing University of Aeronautics and Astronautics. Before joining BUPT, he conducted postdoctoral research at Columbia University, contributing to advancements in wireless communication technologies. His research focuses on wireless communications, heterogeneous networking, underwater acoustics, and AI-driven optimization, particularly in areas such as federated learning, intelligent reflecting surfaces, and 6G network design. As a prolific and highly cited researcher, Dr. Zhang has co-authored more than forty IEEE journal papers in collaboration with leading international scholars. His publication record includes 59 documents cited by 967 other documents, totaling 1,207 citations. He has served as an Associate Editor for Electronics Letters and a Review Editor for Frontiers in Communications and Networks. His excellence has been recognized through numerous honors, including the Boosting Project Award for Young Talents from the China Association for Science and Technology, multiple IEEE Best Paper Awards, and the Science and Technology Awards from the China Institute of Communications and the Radio Association of China. His work bridges theory and application, advancing intelligent, energy-efficient communication systems and inspiring innovation within the global telecommunications community.

Profile : Scopus | ORCID 

Featured Publications 

Zhang, H., Yang, L.-L., & Hanzo, L. (2016). Performance analysis of OFDM systems in dispersive indoor power line channels. IET Communications. [Cited by 35]

Zhang, H., Jiang, C., & Hanzo, L. (2019). Linear precoded index modulation. IEEE Transactions on Communications. [Cited by 120]

Zhang, H., & Hanzo, L. (2020). Federated learning assisted multi-UAV networks. IEEE Transactions on Vehicular Technology. [Cited by 90]

Jiang, H., Xiong, B., & Zhang, H. (2023). Hybrid far- and near-field modeling for RIS assisted V2V channels. IEEE Transactions on Wireless Communications. [Cited by 45]

Zhang, H., et al. (2024). Space-time shift keying aided OTFS modulation for orthogonal multiple access. IEEE Transactions on Communications. [Cited by 20]

Belkacem Bekhiti | Engineering | Best Researcher Award

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Prof. Belkacem Bekhiti | Engineering | Best Researcher Award

Prof. Belkacem Bekhiti | Institute of Aeronautics and Space Studies, University of Blida | Algeria

Dr. Bekhiti Belkacem is a distinguished academic and researcher in control theory, robotics, and aerospace engineering, currently serving as a Lecturer at the Institute of Aeronautics and Space Studies, Blida University 1, Algeria. His expertise spans guidance, navigation, and control systems, integrating theoretical modeling with real-world aerospace applications. He holds a Doctorate in Electrical Engineering with a specialization in Automatic Control from the University of Boumerdes, a Magister in Advanced Control of Complex Systems from the National Polytechnic School, Oran, a Master’s in Automatic Control from the University of Djelfa, and an Engineering degree in Electrical Engineering from Boumerdes. His career includes teaching positions at Blida and Djelfa Universities, collaboration with the Algerian Air Agency, and supervision of advanced student projects in UAVs, satellite control, and robotics. His research focuses on MIMO control, matrix polynomial theory, robotic modeling, nonlinear adaptive control, and intelligent aerospace system design, merging classical automation with artificial intelligence and fractional-order control. He has authored several books and numerous international publications, presented his work at major conferences, and earned recognition for his contributions to intelligent control and aerospace systems. His influence extends across the Algerian and international research communities, where he continues to inspire innovation and academic excellence in modern control and aeronautical engineering.

Profile : Google Scholar 

Featured Publications 

  • Bekhiti, B. (2015). On the theory of λ-matrices based MIMO control system design. Control and Cybernetics.

  • Bekhiti, B. (2017). Intelligent block spectral factors relocation in a quadrotor UAV. International Journal of Scientific Computing (IJSCC).

  • Bekhiti, B. (2018). On λ-matrices and their applications in MIMO control systems design. International Journal of Mathematical and Computational Intelligence (IJMIC).

  • Bekhiti, B. (2020). On the block decomposition and spectral factors of λ-matrices. Control and Cybernetics.

  • Bekhiti, B. (2020). Internal stability improvement of a natural gas centrifugal compressor. Journal of Natural Gas Science and Engineering.

Jingyi Gao | Engineering | Best Researcher Award

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Ms. Jingyi Gao | University of Virginia | United States

Ms. Jingyi Gao | University of Virginia | United States

Jingyi Gao is a Ph.D. candidate in Systems and Information Engineering at the University of Virginia with a 3.75 GPA, focusing on time series prediction, Bayesian probabilistic modeling, and federated learning. She holds an M.S. in Applied Mathematics and Statistics from the Johns Hopkins University (GPA 3.9) and dual bachelor’s degrees in Mathematics–Computer Science and Economics from the University of California, San Diego. Jingyi has extensive teaching experience, serving as a teaching assistant at UVA where she has instructed over 1,000 students across multiple courses in statistical modeling, data mining, AI, and big data systems, and previously supported courses at Johns Hopkins and UC San Diego. She has mentored underrepresented students through the Data Justice Academy and completed research internships at the University of Pittsburgh and Tencent, developing machine learning models for stress detection, healthcare data analysis, and cloud resource forecasting. Jingyi has authored several publications, including work accepted by Pattern Recognition and under review at AAAI and IISE Transactions. Her recent projects involve designing deep latent variable models for ergonomic risk assessment, developing real-time adaptive prediction frameworks for occupational health monitoring, creating federated learning approaches for multi-output Gaussian processes, and modeling behavioral regularity and predictability from multidimensional sensing signals. Combining expertise in machine learning, statistical modeling, and data-driven decision systems, Jingyi aims to advance human-centered intelligent systems through interpretable and privacy-preserving predictive modeling.

Profile: Scopus | Google Scholar

Featured Publications 

Gao, J., Rahman, A., Lim, S., & Chung, S. TimeSets: A real-time adaptive prediction framework for multivariate time series (Manuscript under review at the Association for the Advancement of Artificial Intelligence).

Gao, J., Lim, S., & Chung, S. Gait-based hand load estimation via deep latent variable models with auxiliary information (Manuscript under review at IISE Transactions).

Gao, J., & Chung, S. Federated automatic latent variable selection in multi-output Gaussian processes (Accepted for publication in Pattern Recognition)*.

Gao, J., Yan, R., & Doryab, A. Modeling regularity and predictability in human behavior from multidimensional sensing signals and personal characteristics. Proceedings of the International Conference on Machine Learning and Applications (ICMLA). Institute of Electrical and Electronics Engineers.

Chen, T., Chen, Y., Gao, J., Gao, P., Moon, J. H., Ren, J., … & Woolf, T. B. Machine learning to summarize and provide context for sleep and eating schedules. bioRxiv.