Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

Dr. Vikas Mehta | Statistical Computing and Programming | Research Excellence Award

Korean National Institute for International Education | South Korea

Dr. Vikas Mehta is a structural engineer and researcher specializing in seismic performance optimization, sustainable construction materials, and the application of advanced computational and machine learning methodologies to civil infrastructure systems. He completed his Ph.D. in Civil Engineering at Keimyung University, South Korea, where his award-winning doctoral research introduced innovative modifier-based and data-driven techniques for improving shear strength prediction and design accuracy in reinforced concrete beam-column joints. His expertise spans nonlinear finite element modeling, fragility analysis, physics-informed and graph-based machine learning, geospatial analytics, and performance-based seismic assessment, supported by strong proficiency in ETABS, OpenSees, SeismoSoft, Abaqus, MATLAB, Q-GIS, SPSS, Python, PyTorch, WEKA, and OriginPro. Dr. Mehta serves as a Postdoctoral Researcher at the Chonnam National University R&BD Foundation, contributing to advanced safety technologies for nuclear power plant structures under extreme hazard scenarios, including buckling resistance enhancement, retrofit optimization, and complex wind–terrain interaction studies. His professional background includes academic appointments in structural and construction engineering, where he taught subjects in earthquake engineering, finite element analysis, and structural systems while supervising graduate research and contributing to curriculum and laboratory development. Dr. Mehta has authored a substantial body of SCI-indexed research on seismic damage prediction, torsional behavior modeling, hybrid AI-mechanics frameworks, recycled and sustainable materials, computational methods, and structural performance evaluation, complemented by multiple patents in construction materials, damping devices, and waste-based composites. He has presented at leading international and national conferences and contributed to funded collaborative research, including projects involving global academic and industry partners. His professional affiliations include membership in ASCE, the Institute of Physics (AMInstP), IAEME (Fellow), and licensure as a Class-A engineer under the Himachal Pradesh Town and Country Planning Act. Dr. Mehta’s contributions to structural engineering and computational mechanics continue to gain international visibility, reflected in an h-index of 7, over 172 citations, and more than 19 published documents, underscoring his growing influence in machine learning–driven structural design, seismic resilience, and sustainable construction innovation.

Profiles: Scopus | Orcid

Featured Publications

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Corrigendum to “Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints”.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Predictive framework for shear strength and failure modes of exterior reinforced concrete beam–column joints using machine learning. Structural Concrete. h.

Sagar, G. S., Mukthi, S., & Mehta, V. (2025). Analyzing compressive, flexural, and tensile strength of concrete incorporating used foundry sand: Experimental and machine learning insights. Archives of Computational Methods in Engineering.

Mehta, V., Thakur, M. S., & Chey, M. H. (2025). Enhancing seismic design accuracy of RC beam-column joints: Modifier-based approach for shear strength predictions. Structures.

Mehta, V., Jang, S. H., & Chey, M. H. (2025). Adaptive simulation and data-driven hybrid modeling for predicting shear strength and failure modes of interior reinforced concrete beam-column joints. Structures.

Jianjian Chen | Operations Research and Statistical Optimization | Operations Research Award

Dr. Jianjian Chen | Operations Research and Statistical Optimization | Operations Research Award

 Jiangxi University of Finance and Economics | China

Dr. Jianjian Chen is a lecturer in the School of Information Management and Mathematics at Jiangxi University of Finance and Economics, Jiangxi, P. R. China, where he has established himself as a promising scholar in the fields of management science, decision support, and electronic commerce. His research focuses on platform economics, online marketplaces, and decision support methodologies that contribute to both the theoretical and practical advancement of information systems and business strategies. Over the course of his career, Chen has built a solid portfolio of high-quality research, with his work appearing in well-regarded journals including Decision Support Systems, Information Systems Frontiers, Computers & Industrial Engineering, Electronic Commerce Research, and Electronic Commerce Research and Applications. These publications highlight his expertise in applying analytical and empirical methods to understand the complexities of digital platforms and e-commerce ecosystems. According to his Scopus profile Chen has published 7 scholarly documents, which have collectively received 86 citations, resulting in an h-index of 5, reflecting both the productivity and the impact of his research. His contributions not only enrich the academic discourse on decision support and electronic commerce but also offer practical insights for businesses navigating digital transformation and platform-based economies. Chen’s scholarship demonstrates a balance between rigorous methodological development and the application of innovative models to real-world problems, reinforcing his role as a valuable contributor to the intersection of management, information systems, and economics. By combining theoretical frameworks with practical problem-solving approaches, his research provides meaningful support for decision-making in the digital economy and underscores his growing influence within the international academic community.

Profile: Scopus 

Featured Publications

“Traditional e-commerce or live e-commerce? Online sales model selection strategies considering streamers’ bargaining behaviors”