Jongwoo Min | Tourism Management | Research Excellence Award

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Mr. Jongwoo Min | Tourism Management | Research Excellence Award

Chief Financial Officer (CFO) | Kangil Tour | South Korea

Mr. Jongwoo Min is a researcher in tourism management and digital transformation whose work focuses on organizational learning, problem-solving competency, and organizational effectiveness in online travel agencies (OTAs). His peer-reviewed publication in Sustainability (SSCI) empirically demonstrates how digital empowerment moderates the relationship between learning systems and organizational performance, offering a data-driven framework for service-sector transformation. His research portfolio also includes applied public-sector studies on regional tourism sustainability, accessibility, and operational strategy, including the Jarasum Namdo Flower Festival academic study, Smart Barrier-Free tourism research, mountain tourism feasibility analysis, and integrated operational planning for leisure and water sports facilities. These projects collectively advance sustainable tourism development through evidence-based policy and industry integration. His work bridges academic theory and real-world tourism systems by combining quantitative modeling with government and industry data, contributing to innovation in digital tourism ecosystems, inclusive service design, and regional tourism competitiveness.

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Davron Juraev | Data Modeling and Database Design | Research Excellence Award

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Prof. Dr. Davron Juraev | Data Modeling and Database Design | Research Excellence Award

Research Fellow | Turon University | Uzbekistan

Prof. Dr. Davron Juraev is an internationally published mathematician whose research centers on ill-posed problems, elliptic systems, Cauchy problems, Helmholtz equation factorizations, mathematical physics, numerical analysis, and applied mathematical modeling. According to Google Scholar, he has 1,532 citations, 284 indexed documents, an h-index of 23, and an i10-index of 41, reflecting sustained global impact. His scholarship spans high-visibility journals and proceedings in mathematical physics, fractional calculus, spectral theory, computational mathematics, data analysis, and engineering applications, with extensive contributions to Helmholtz theory, regularization methods, and matrix factorization techniques. He has authored multiple research monographs and book chapters with international publishers, edited special issues in mathematical physics, and published across interdisciplinary domains including engineering systems, quantum decision models, and applied data sciences. His funded research leadership includes fundamental national and international collaborative projects, while his editorial board memberships, guest editorships, and reviewer service demonstrate recognized authority within the global applied mathematics and computational sciences community.

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Kunyuan Li | Data Modeling and Database Design | Research Excellence Award

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Dr. Kunyuan Li | Data Modeling and Database Design | Research Excellence Award

Ph.D. Candidate | Army Engineering University of PLA | China

Dr. Kunyuan Li is an emerging interdisciplinary researcher whose work bridges mathematical theory and computational modeling, with a focus on fractal geometry, fractional calculus, and complex systems analysis. According to Scopus metrics, he holds 9 citations, 1 indexed document, and an h-index of 1, reflecting early but growing scholarly impact. His peer-reviewed publications in high-impact Q1 journals such as Fractals, Chaos, Solitons & Fractals, and Fractal and Fractional advance theoretical frameworks for self-affine curves, Hausdorff dimensions, and biological collective dynamics. His research contributions integrate numerical analysis, data-driven modeling, and artificial intelligence, supporting innovation across mathematics, nonlinear systems, and computational science.

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Peiyun Zhang | Solid Mechanics | Excellence in Research Award

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Mr. Peiyun Zhang | Solid Mechanics | Excellence in Research Award

Shenzhen University | China

Mr. Peiyun Zhang’s research focuses primarily on the fracture and fatigue behavior of structural materials, with particular emphasis on high-strength steels and composite-reinforced concrete elements. His work delivers quantitative insights into ductile fracture mechanisms, integrating experimental testing with advanced numerical modeling to enhance the predictive accuracy of failure assessments in structural steels. Mr. Peiyun Zhang has contributed significantly to understanding the ductile fracture behavior of Q460C high-strength steel, employing monotonic loading experiments and MMC-based fracture modeling to evaluate damage evolution and fracture initiation under diverse stress states. His studies provide unified methodologies for predicting fracture across various steel grades, enabling more reliable performance evaluations of structural components subjected to extreme mechanical demands. In addition to steel fracture, he has examined fatigue behavior in concrete beams reinforced with CFRP rebars and investigated the influence of different web-anchorage configurations on structural durability. This cohesive body of work advances structural safety design, strengthens material reliability assessments, and supports national-level extreme disaster assessment and mitigation efforts by enabling accurate prediction of failure in large-scale structural systems.

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Featured Publications

  • Chen, A., Zhang, P., Chen, B., Li, Y., & Xing, J. (2023). A new ductile fracture model for Q460C high-strength structural steel under monotonic loading: Experimental and numerical investigation. Engineering Fracture Mechanics, 288, 109358.

  • Chen, A., Zhang, P., Lin, J., & Xing, J. (2023). Study on ductile fracture of Q460C high-strength structural steel based on MMC fracture model. Engineering Mechanics.

  • Zhang, P. Y., Kim, O. Y., & Cui, X. (2019). Fatigue behavior of concrete beam using CFRP rebar. Journal of the Korea Institute of Building Construction, 19(6), 495–501.

  • Zhang, P., Chen, A., Xing, J., & Wang, Y. (2025). New unified model for predicting ductile fracture in structural steels. International Journal of Mechanical Sciences, Article 111085.

  • Cui, X., & Zhang, P. Y. (2019). Fatigue effect of the type of web anchorage in RC beams bonded with CFRP plate. Journal of the Korean Society for Advanced Composite Structures, 10(6), 21–27.

Hongtao Li | Cyberspace Security | Best Researcher Award

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Prof. Dr. Hongtao Li | Cyberspace Security | Best Researcher Award

Linyi University | China

Prof. Dr. Hongtao Li is a distinguished researcher specializing in cryptography and its applications, IoT security, large model security, and AI security. He serves as a council member of the Shanxi Computer Society and has been recognized under the “Sanjin Talent” Support Program in Shanxi Province. His research contributions encompass privacy-preserving mechanisms for big data, federated learning, blockchain-based auditing, and secure data collection for smart cities and IoT systems. He has led multiple high-profile projects, including a National Natural Science Foundation of China Youth Project on big data security and privacy protection, and several provincial-level initiatives focused on IoT security, medical big data protection, and cyberspace education reform. Prof. Li holds two authorized patents for computer network security and information security devices, reflecting his strong applied research impact. He has published over 50 papers in high-impact journals, addressing differential privacy, location privacy, blockchain protocols, and privacy-preserving schemes for digital communities and healthcare systems. His work demonstrates a consistent focus on safeguarding data and enhancing security frameworks in complex networked environments. With an h-index of 11, 328 citations by 314 documents, and 30 scholarly publications, Prof. Li’s research has significantly influenced both theoretical and applied aspects of cybersecurity, particularly in IoT and large-scale data environments, positioning him as a leading figure in advancing secure and privacy-preserving technologies in China and internationally.

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Featured publications

  • Wang, J., Zhang, Z. J., Tian, J., & Li, H. T. (2024). Local differential privacy federated learning based on heterogeneous data multi-privacy mechanism. Computer Networks, 254, 110822.

  • Li, H. T., Ma, J. F., & Fu, S. (2015). A privacy-preserving data collection model for digital community. Science China Information Sciences, 58(3), 1–16.

  • Li, H. T., Guo, F., & Wang, L., et al. (2021). A blockchain-based public auditing protocol with self-certified public keys for cloud data. Security and Communication Networks, 2021(3), 1–10.

  • Li, H. T., Wang, Y., & Guo, F., et al. (2021). Differential privacy location protection method based on the Markov model. Wireless Communications and Mobile Computing, 2021, 1–10.

  • Li, H. T., Xue, X., Li, Z., et al. (2021). Location privacy protection scheme for LBS in IoT. Wireless Communications and Mobile Computing, 2021, 1–18.