Bilal Ahmad | Computational Metallurgy | Research Excellence Award

Mr. Bilal Ahmad | Computational Metallurgy | Research Excellence Award

University of Johannesburg | South Africa

Mr. Bilal Ahmad demonstrates emerging excellence in data science and artificial intelligence, with scholarly focus on machine learning and deep learning applications for complex, real-world problems. Research contributions emphasize predictive analytics and intelligent modeling, including peer-reviewed work on epidemic outbreak analysis using advanced computational techniques. The research reflects methodological soundness, interdisciplinary relevance, and alignment with current global challenges in data-driven systems. According to the Scopus profile, the researcher has 1 indexed publication, 2 total citations, and an h-index of 1, indicating early academic visibility and growing research impact. These contributions highlight strong potential for continued advancement and research excellence.

Citation Metrics ( Google Scholar )

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Citations
2

Documents
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h-index
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Featured Publications


Exploration of Epidemic Outbreaks Using Machine and Deep Learning Techniques
– Advances in Cybersecurity, Cybercrimes, and Smart Emerging Technologies, 2023

Zhi Zong | Computational Mechanics | Best Researcher Award

Prof. Dr. Zhi Zong | Computational Mechanics | Best Researcher Award

Professor at Fuyao University of Science and Technology | China

Prof. Dr. Zhi Zong is a leading researcher whose work integrates structural mechanics, fluid dynamics, computational modeling, and probabilistic engineering to advance the understanding of complex marine and mechanical systems. With 5,620 citations, 334 research documents, and a Scopus h-index of 38, his publications demonstrate both volume and influence within international scientific communities. His contributions include formulating high-accuracy Differential Quadrature (DQ) computational methods, such as localized, complex, and variable-order DQ techniques, which have improved the numerical simulation capabilities used in ocean engineering, ship mechanics, and structural analysis. He has made pioneering advances in uncertainty quantification, notably by identifying the variability of ship structural vibrations caused by geometric imperfections and by developing an asymptotically unbiased entropy estimator for probability distribution modeling-an outcome that has strengthened probabilistic mechanics applications. His Random Pore Model for sea ice represents an important development in capturing realistic mechanical and physical behaviors of ice, contributing to engineering design, climate studies, and environmental modeling. Beyond these theoretical achievements, Professor Zong has authored over 230 SCI-indexed papers and several specialized monographs addressing complex topics such as underwater explosion modeling, isolated water waves, and bubble dynamics. His research has been incorporated into practical marine engineering solutions and serves as a foundation for ongoing advancements in computational methods and ocean systems design. His body of work demonstrates consistent innovation, scientific rigor, and global relevance, making him a strong candidate for recognition under the Best Researcher Award.

Profiles : Scopus | Google Scholar

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. Cited by: 370.

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. Cited by: 324.

Zong, Z., & Zhang, Y. (2009). Advanced differential quadrature methods. Chapman and Hall/CRC. Cited by: 259.

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. Cited by: 257.

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. Cited by: 155.