Shougui Zhang | High Performance Computing | Best Researcher Award

Published on by Computer Science Engineering

Prof. Dr. Shougui Zhang | High Performance Computing | Best Researcher Award

Teacher |Chongqing Normal University| China

Prof. Dr. Shougui Zhang is a distinguished scholar whose academic contributions focus primarily on computational mathematics, particularly in the field of numerical analysis and applied mathematics. His extensive research explores the numerical solution of partial differential equations (PDEs), an area that forms the foundation of many scientific and engineering applications. Zhang has made notable progress in the development and refinement of boundary element methods, which are efficient numerical techniques for solving boundary value problems that arise in physics and engineering disciplines such as fluid dynamics, elasticity, and electromagnetism. His work emphasizes mathematical rigor combined with computational efficiency, aiming to provide stable and accurate algorithms for complex real-world systems. A major aspect of his research involves variational inequalities, where he investigates computational methods for handling inequality constraints that frequently appear in optimization, contact mechanics, and obstacle problems. Zhang’s studies in this area contribute to bridging theoretical mathematical formulations with practical computational tools, enabling more precise simulations and analyses of nonlinear and constrained physical systems. His contributions extend beyond methodological innovation, influencing the design of advanced algorithms that improve the performance of numerical solvers and support the development of scientific computing frameworks. Over the years, he has published numerous research papers in recognized journals, reflecting a strong engagement with the global mathematical community. His interdisciplinary approach, combining mathematical theory, numerical techniques, and computational experimentation, enhances the understanding and application of PDE-based models across diverse domains. Zhang’s ongoing investigations into computational variational inequalities mark an important direction in applied mathematics, where numerical precision and computational feasibility must coexist. His research continues to play a key role in advancing the field of computational mathematics, fostering collaborations and innovative applications in scientific and engineering contexts. He has achieved 362 citations, authored 33 documents, and holds an h-index of 11.

Profiles: Scopus | ORCID
Featured Publication

Author(s). (2025). A self-adaptive alternating direction multiplier method for variational inequality in 2 domains. Applied Mathematics and Mechanics.

Author(s). (2025). Analysis of a Crank–Nicolson fast element-free Galerkin method for the nonlinear complex Ginzburg–Landau equation. Journal of Computational and Applied Mathematics. 7 Citations.

Author(s). (2024). Self-adaptive alternating direction method of multiplier for a fourth order variational inequality. Journal of Inequalities and Applications.

Mustafa Namdar | High Performance Computing | Best Researcher Award

Published on by Computer Science Engineering

Assoc. Prof. Dr . Mustafa Namdar | High Performance Computing | Best Researcher Award

Assoc. Prof. Dr | Kutahya Dumlupinar University| Turkey

Dr. Mustafa Namdar has established a distinguished research profile in advanced wireless communications and network technologies, focusing on cognitive radio networks, cooperative communications, relay networks, interference alignment, non-orthogonal multiple access (NOMA), reconfigurable intelligent surfaces (RIS), and integrated sensing and communication (ISAC). His work emphasizes innovative solutions to enhance spectral efficiency, reliability, and performance in next-generation communication systems. Dr. Namdar has contributed extensively to the development of receiver diversity and dispersed spectrum sensing techniques, enabling efficient utilization of available spectrum and minimizing interference in dynamic network environments. His research integrates theoretical modeling with practical system design, addressing complex challenges in 5G and emerging 6G wireless technologies. He has actively collaborated on projects related to cooperative relay networks and interference management, which are critical for optimizing throughput and ensuring robust connectivity in dense network scenarios. In addition to his contributions to physical layer design, Dr. Namdar explores the potential of reconfigurable intelligent surfaces and ISAC frameworks to simultaneously support communication and sensing functionalities, offering a transformative approach for intelligent wireless networks. His work has been recognized through multiple awards, including the Outstanding Reviewer Award from Elsevier-AEU Journal and IEEE SIU Conference accolades, reflecting both the quality and impact of his research in the international community. Dr. Namdar’s expertise in NOMA and interference alignment provides practical solutions for multi-user communication scenarios, significantly advancing spectral efficiency and network capacity. He has also played a pivotal role in the technical evaluation of numerous research projects and has contributed as a reviewer and TPC member across prestigious IEEE conferences and journals, ensuring high standards in scholarly communications. His ongoing research aims to drive the evolution of future wireless networks with integrated sensing, enhanced resource allocation, and next-generation communication protocols. 272 Citations, 54 Documents, 10 h-index, View h-index.

Profiles:  Google Scholar | Scopus
Featured Publication

Alakoca, H., Namdar, M., Aldırmaz-Çolak, S., Basaran, M., Basgumus, A., & … (2023). Metasurface manipulation attacks: Potential security threats of RIS-aided 6G communications. IEEE Communications Magazine, 61(1), 24–30. 43 citations

Bayhan, E., Ozkan, Z., Namdar, M., & Basgumus, A. (2021). Deep learning based object detection and recognition of unmanned aerial vehicles. 2021 IEEE 3rd International Congress on Human-Computer Interaction. 41 citations

Ozkan, Z., Bayhan, E., Namdar, M., & Basgumus, A. (2021). Object detection and recognition of unmanned aerial vehicles using Raspberry Pi platform. 2021 IEEE 5th International Symposium on Multidisciplinary Studies and … 34 citations

Namdar, M., & Ilhan, H. (2018). Exact closed-form solution for detection probability in cognitive radio networks with switch-and-examine combining diversity. IEEE Transactions on Vehicular Technology, 67(9), 8215–8222. 23 citations

Namdar, M., Ilhan, H., & Durak-Ata, L. (2016). Optimal detection thresholds in spectrum sensing with receiver diversity. Wireless Personal Communications, 87, 63–81. 23 citations

Umakoglu, I., Namdar, M., Basgumus, A., Kara, F., Kaya, H., & Yanikomeroglu, H. (2021). BER performance comparison of AF and DF assisted relay selection schemes in cooperative NOMA systems. 2021 IEEE International Black Sea Conference on Communications and … 22 citations