Ling Xu | Engineering | Young Scientist Award | 4273

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Assoc. Prof. Dr. Ling Xu | Engineering | Young Scientist Award

Teacher | Fuzhou University | China

Assoc. Prof. Dr. Ling Xu is an Associate Professor at the College of Civil Engineering, Fuzhou University, specializing in transportation infrastructure construction, pavement materials, and maintenance engineering. He holds a doctorate in Transportation Engineering, a visiting scholarship in civil infrastructure research, and a bachelor’s degree in Civil Engineering, providing a solid academic foundation in pavement mechanics, material behavior, and life-cycle performance. His professional experience includes contributing to national and industry-funded projects on polyurethane concrete runway overlays, rubberized asphalt durability, high RAP mixture cracking mechanisms, high-speed railway waterproofing layers, and flexible interlayer systems for airfield pavements. His research focuses on low-carbon pavement materials, road maintenance technologies, numerical simulation, data mining, image processing, and life-cycle analysis, leading to impactful publications in high-ranking international journals on asphalt modification, pavement sustainability, thermal-mechanical behavior, and innovative maintenance materials. Recognized with a Young Scientist Award, he has also contributed to the academic community through editorial and review activities, professional memberships, and active participation in interdisciplinary research collaborations.

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Featured Publications

Chang Soo Kim | Engineering | Best Researcher Award

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Prof. Chang Soo Kim | Engineering | Best Researcher Award

Professor | Pukyong National University | South Korea

Professor. Chang Soo Kim is a distinguished Full Professor in the Division of Computer and AI Engineering at PuKyong National University, recognized for his expertise in intelligent manufacturing systems, artificial intelligence, and computational optimization. He holds advanced degrees in computer science with specialization in AI-driven optimization and machine learning, forming the foundation for his multidisciplinary research career. Throughout his long-standing academic tenure, he has served in key leadership roles including department chair, graduate program administrator, research center director, and executive leader for university–industry cooperation, successfully guiding large-scale projects, fostering collaborative innovation, and advancing strategic academic initiatives. His research focuses on flexible job shop scheduling, deep learning–based fault diagnosis, time-series forecasting, metaheuristic optimization, and smart industrial systems. He has produced an extensive portfolio of influential publications in high-impact SCI-indexed journals, contributing novel hybrid algorithms, trainable fusion strategies, adaptive scheduling frameworks, lightweight diagnostic models, and intelligent computational methods that support the evolution of smart manufacturing and data-driven engineering. His scholarly achievements have earned him multiple recognitions, including awards for research excellence, and he actively contributes to the global academic community through editorial service, participation in professional societies, and engagement in scientific committees. With a sustained record of innovative research, academic leadership, and impactful contributions to computer and AI engineering, Professor Chang Soo Kim exemplifies the qualities of a leading researcher whose work continues to influence both industry and academia.

Profiles:  Scopus

Featured Publications

1. Kim, C. S., et al. (2025). Flexible job shop scheduling optimization with multiple criteria using a hybrid metaheuristic framework. Processes.

2. Kim, C. S., et al. (2025). Multi-branch global Transformer-assisted network for fault diagnosis. Applied Soft Computing.

3. Kim, C. S., et al. (2025). DL-MSCNN: A general and lightweight framework for fault diagnosis with limited training samples. Journal of Intelligent Manufacturing.

4. Kim, C. S., et al. (2025). Enhanced quantum-based DNA sequence alignment with noise handling and error detection. IEEE Access.

5. Kim, C. S., et al. (2024). GAILS: An effective multi-object job shop scheduler based on genetic algorithm and iterative local search. Scientific Reports.

Professor Chang Soo Kim’s pioneering research in intelligent manufacturing, AI-driven optimization, and fault diagnosis advances the scientific foundations of smart industry while enabling more efficient, reliable, and data-driven production systems. His innovative computational frameworks and adaptive algorithms contribute directly to industrial digital transformation, fostering technological competitiveness and sustainable global innovation.

Liheng Wu | Engineering | Best Paper Award

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Ms. Liheng Wu | Engineering | Best Paper Award

postdoc researcher, Southeast University, China

Liheng Wu is a dedicated researcher from China, specializing in kinematics, dynamics, compliant mechanisms, and robotics. Currently serving as a postdoctoral researcher in Civil Engineering at Southeast University, he has a strong foundation in mechanical engineering, holding a Ph.D. from Tianjin University. Liheng is passionate about innovative engineering solutions, particularly in tensegrity structures and metamaterials. 🌍🔧

Publication Profile

Scopus

Strengths for the Award

  1. Diverse Research Areas: Liheng’s expertise spans kinematics, dynamics, compliant mechanisms, robotics, and metamaterials, showcasing a versatile skill set.
  2. Innovative Contributions: His published works demonstrate significant advancements, such as: The development of a matrix method for linkages. Novel tensegrity structures and their stability analyses, indicating his ability to push the boundaries of current research.
  3. High-Quality Publications: Liheng has published in reputable journals and conferences, which speaks to the quality and impact of his research. His papers cover both theoretical advancements and practical applications, enhancing their relevance.
  4. Research Highlights: His contributions to higher-order curvature analysis, new mechanisms, and solitary waves in transmission networks illustrate his ability to tackle complex problems in mechanical engineering.

Areas for Improvement

  1. Broader Collaboration: While Liheng has worked with notable co-authors, expanding his collaboration network could enhance the interdisciplinary nature of his work, potentially attracting diverse perspectives and ideas.
  2. Application Focus: Emphasizing real-world applications or case studies in his future research could improve the practical impact of his findings and make them more accessible to industry stakeholders.
  3. Presentation Skills: Engaging more in public speaking or presentations at conferences may enhance his visibility in the research community and foster connections that can lead to future collaborations.

Education

Liheng completed his Ph.D. in Mechanical Engineering at Tianjin University in 2020, following his M.S. from Hebei University of Technology in 2013 and a B. Eng. from Chongqing Business and Technology University in 2010. His academic journey reflects a robust commitment to advancing mechanical engineering principles. 🎓📚

Experience

Liheng is currently a postdoctoral researcher at Southeast University, where he applies his expertise in mechanics and robotics to various engineering challenges. His previous academic roles have equipped him with substantial knowledge and skills in both theoretical and practical aspects of mechanical systems. 🛠️💼

Research Focus

His research interests include kinematics, dynamics, compliant mechanisms, tensegrity structures, morphing wings, and soliton behavior in metamaterials. Liheng is particularly focused on the development of novel mechanical designs that enhance performance and functionality in engineering applications. 🔍✨

Awards and Honours

Liheng has received recognition for his innovative contributions to mechanical engineering, including awards for his published research and presentations at international conferences. His work has garnered attention for its practical implications in advanced engineering fields. 🏆🌟

Publication Top Notes

A matrix method to determine infinitesimally mobile linkages with only first-order infinitesimal mobility (2020, Mechanisms and Machine Theory)

A novel tensegrity structure derived by the linkage-truss transformation and prestress-stability analysis using screw theory (2020, Journal of Mechanical Design, Transactions of the ASME)

Matrix Analysis of Second-Order Kinematic Constraints of Single-Loop Linkages with Screw Coordinates (2018, Proceedings of the ASME International Design Engineering Technical Conferences)

Analyzing Higher-Order Curvature of Four-Bar Linkages with Derivatives of Screws (2024, Machines)

Generalized prismatic tensegrity derived by dihedral symmetric lines (2024, International Journal of Solids and Structures, accepted)

Conclusion

Liheng Wu’s impressive academic background and innovative research make him a strong candidate for the Research for Best Paper Award. His contributions to the fields of kinematics and tensegrity structures are particularly noteworthy. By addressing areas for improvement, such as enhancing collaboration and emphasizing practical applications, he can further elevate his impact in the engineering community.