Sang-Su Lee | Engineering | Best Researcher Award

Best Researcher Award

Sang-Su Lee
Korean Register, Busan, South Korea
Sang-Su Lee
Affiliation Korean Register
Country South Korea
Scopus ID 58871667800
Documents 2
Citations 60
h-index 2
Subject Area Engineering
Event International Popular Scientist Awards

Sang-Su Lee is an engineering researcher affiliated with Korean Register in Busan, South Korea, whose indexed research includes marine engineering, ship propulsion systems, energy-efficiency regulations, shafting safety, and maritime decarbonization. The available Scopus profile information identifies two indexed documents, 60 citations, and an h-index of 2.[1]

Abstract

Sang-Su Lee’s indexed research reflects an engineering focus on maritime propulsion, ship energy efficiency, and the safety implications of technical modifications introduced to meet contemporary environmental-performance requirements. A notable 2024 article in Results in Engineering evaluates a redesigned shafting system following a propeller redesign intended to improve CII and EEXI performance. The study considers a 6500 TEU container ship and examines engine power limitations, torsional vibration, and shaft alignment to assess the safety of the modified propulsion arrangement. [1]

Keywords

Sang-Su Lee; Best Researcher Award; marine engineering; ship propulsion; shafting systems; propeller redesign; CII; EEXI; torsional vibration; shaft alignment; maritime decarbonization; energy efficiency; Korean Register.

Introduction

Maritime transportation is undergoing significant technical and regulatory changes aimed at improving energy efficiency and reducing greenhouse-gas emissions. International maritime regulations have introduced performance indicators including the Energy Efficiency Existing Ship Index (EEXI) and Carbon Intensity Indicator (CII), creating engineering requirements that affect propulsion-system design and vessel operation. Lee’s research addresses this intersection between regulatory performance and mechanical engineering by examining how modifications intended to improve vessel efficiency influence shafting-system safety. [1]

Research Profile

Lee’s documented research profile is situated within engineering applications related to maritime systems. His published work connects ship energy-efficiency requirements with propulsion-system analysis, particularly where changes to propeller or engine configurations can influence mechanical loads and shafting performance. The research therefore occupies an interdisciplinary position between marine engineering, mechanical-system safety, and environmental performance.

Research Contributions

The principal documented contribution concerns the engineering assessment of a redesigned shafting system implemented following propeller redesign intended to improve CII and EEXI performance. The study examined a 6500 TEU container ship and determined engine power limitations under EEXI-related requirements before assessing the resulting implications for CII. The redesigned shafting system was subsequently evaluated through torsional-vibration calculations and shaft-alignment analyses. [1]

Publications

The supplied Scopus record identifies two indexed documents for Sang-Su Lee. One documented publication is the 2024 open-access article listed below.

  1. Lee, Sang-Su. “Evaluating the safety of the redesigned shafting system following the propeller redesign aimed at enhancing CII and EEXI.” Results in Engineering, volume 23, September 2024, article 102352.[1]

Research Impact

According to the supplied researcher profile, Lee’s work has accumulated 60 citations across two indexed documents, with an h-index of 2. Bibliometric indicators can provide a quantitative indication of scholarly visibility, although they do not by themselves establish research quality or significance. In this context, the documented publication addresses a practical engineering problem relevant to ship operators, propulsion-system designers, classification and technical organizations, and researchers studying maritime energy efficiency.

Award Suitability

Sang-Su Lee’s documented research profile provides a relevant basis for consideration for the Best Researcher Award under the International Popular Scientist Awards. The basis for consideration includes an identifiable engineering research record, indexed scholarly publications, citation activity, and research addressing contemporary challenges in maritime propulsion and energy efficiency. [1]

Conclusion

Sang-Su Lee is an engineering researcher affiliated with Korean Register whose documented scholarly work addresses marine propulsion, shafting-system safety, and vessel energy-efficiency requirements. His 2024 publication on redesigned shafting following propeller redesign provides a concrete example of research connecting CII and EEXI objectives with torsional-vibration and shaft-alignment analysis. [1]

References

  1. Lee, Sang-Su. (2024). Evaluating the safety of the redesigned shafting system following the propeller redesign aimed at enhancing CII and EEXI. Results in Engineering, 23, 102352. Elsevier.
    DOI: https://doi.org/10.1016/j.rineng.2024.102352
  2. Directory of Open Access Journals. (2024). Evaluating the safety of the redesigned shafting system following the propeller redesign aimed at enhancing CII and EEXI. Author: Sang-Su Lee; affiliation information includes Korean Register, Busan, Republic of Korea.
    https://doaj.org/article/3340dc9a80af421f86bc57e253b94603
  3. Elsevier. (n.d.). Scopus author details: Sang-Su Lee, Author ID 58871667800. Scopus.
    https://www.scopus.com/pages/authors/58871667800

Afşin Baran Bayezit | Engineering | Research Excellence Award

Mr. Afşin Baran Bayezit | Engineering | Research Excellence Award

Research Assistant at Istanbul Technical University | Turkey

Research engineer specializing in maritime artificial intelligence and control systems, with strong expertise in reinforcement learning, machine learning, and control theory for autonomous platforms. Demonstrates proficiency in developing and validating intelligent control algorithms using Python, embedded systems, and ROS, with hands-on implementation in real-world and model-scale environments. Contributed to advanced research in ship dynamics, autopilot systems, and safety modeling through data-driven approaches. Experienced in integrating sensors, actuators, and high-performance computing tools to optimize system performance. Professional experience reflects a consistent focus on innovative, experimentally validated solutions for autonomous maritime systems, delivering impactful contributions to intelligent navigation, system efficiency, and safety.

Citation Metrics (Google Scholar)

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Stergios Mavromatis | Engineering | Research Excellence Award

Dr. Stergios Mavromatis | Engineering | Research Excellence Award

Associate Professor | Technical University of Athens | Greece

Dr. Stergios Mavromatis is an academic researcher specializing in transportation engineering with a strong focus on road design safety, vehicle dynamics, and highway geometric design. His research explores vehicle–road interaction, stopping sight distance, and safety performance on complex road alignments to enhance traffic safety. He has contributed extensively through scholarly publications on traffic behavior, infrastructure risk factors, and data-driven safety evaluation methods. His research approach combines analytical modeling, simulation techniques, and empirical analysis to develop effective and practical engineering solutions. His work has had a meaningful impact on improving road safety practices, supporting infrastructure planning, and informing policy and safety assessment frameworks at broader levels.

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Young Won Kim | Engineering | Research Excellence Award

Dr. Young Won Kim | Engineering | Research Excellence Award

Senior Researcher | Korea Institute of Industrial Technology | South Korea

Dr. Young Won Kim is a researcher specializing in advanced manufacturing, smart materials, and energy harvesting technologies, with strong expertise in additive manufacturing, digital twin systems, and nano/micro-fabrication. His research focuses on triboelectric and piezoelectric nanogenerators, sensor development, and AI-driven predictive modeling for smart manufacturing applications. He has contributed extensively to high-impact international journals as both lead and corresponding author, particularly in nanomaterials, flexible electronics, and biomedical scaffolds. With 68 publications, 1,085 citations, and an h-index of 17, his work reflects strong academic impact. His professional experience spans academic and industrial research environments, integrating machine learning, materials science, and mechanical engineering to develop innovative systems for energy, healthcare, and intelligent industrial technologies.

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Mo Jamshidi | Engineering | Best Researcher Award

Prof. Dr. Mo Jamshidi | Engineering | Best Researcher Award

The University of Texas at San Antonio | United States

Prof. Dr. Mo Jamshidi is a globally recognized authority in systems engineering, intelligent systems, and system-of-systems engineering, with seminal contributions spanning soft computing, fuzzy logic, neural networks, robotics, and large-scale complex systems. His research integrates control theory, artificial intelligence, and computational intelligence to address challenges in autonomous systems, energy systems, cloud and cyber-physical infrastructures, and bioinformatics, including influential work on genome-scale metabolic networks. He has played a foundational role in defining and advancing system-of-systems as a discipline, shaping both theoretical frameworks and practical applications. His professional experience reflects sustained leadership in interdisciplinary research, authorship of landmark books, and mentorship that has influenced generations of researchers worldwide.

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Jamal Alotaibi | Engineering | Best Researcher Award

Assist. Prof. Dr. Jamal Alotaibi | Engineering | Best Researcher Award

Department of Computer Engineering, College of Computer, Qassim University, Buraydah, Saudi Arabia.

Dr. Jamal Alotaibi is an accomplished researcher and educator in the field of Computer Engineering. With expertise in IoT, AI, and security, he has contributed significantly to the advancement of Smart Transportation and Vehicle-to-Vehicle (V2V) communication. Currently serving as the Head of the Computer Engineering Department at Qassim University, his work focuses on secure and efficient computing frameworks for the Internet of Vehicles (IoV).

Profile

Google Scholar

Education 🎓

  • Ph.D. in Computer Engineering (2018 – 2022) – Wayne State University, USA

  • M.Sc. in Electrical and Computer Engineering (2016 – 2017) – Wayne State University, USA

  • B.Sc. in Computer Engineering (2008 – 2013) – Qassim University, KSA

Experience 👨‍🏫

  • Qassim University (2022 – Present) – Assistant Professor, now Head of the Computer Engineering Department (2024–Present)

  • Wayne State University (2016 – 2022) – Research Assistant in IoT and Security Labs

  • STC Company (2013) – Network Engineer

  • Consultations:

    • Ford Motor Company (2020 – 2022) – Embedded Systems Consultant for Electric Vehicles

    • Verizon Company (2021–2022) – V2V Infrastructure Consultant

    • City of Detroit (2021–2023) – IoV Consultant

Research Interests 🔬

  • Internet of Vehicles (IoV) and Fog Computing

  • Software-Defined Networking (SDN) for Smart Transportation

  • Blockchain-based Security Solutions

  • Machine Learning for Secure Communication Systems

Awards 🏆

  • Head of IoT Research Lab – Wayne State University

  • Head of Research Committee – Qassim University (2023 – Present)

Publications Top Notes: 📚

SAFIoV: A Secure and Fast Communication in Fog-Based IoV Using SDN and Blockchain

IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), 2021

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A Lightweight and Fog-Based Authentication Scheme for Internet-of-Vehicles

IEEE 12th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEM-CON), 2021

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PPIoV: A Privacy-Preserving Framework for IoV-Fog Using Federated Learning and Blockchain

IEEE World AI IoT Congress, 2022

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Insight into IoT Applications and Common Practice Challenges

Insight Journal, 2022

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A hybrid software-defined networking approach for enhancing IoT cybersecurity with deep learning and blockchain in smart cities

SDN-Enabled Efficient Resource Utilization in a Secure, Trustworthy and Privacy Preserving IOV-Fog Environment