Dr. Naeem Ullah | Fluid Dynamics | Research Excellence Award

Research Associate | Yangzhou University | China

Dr. Naeem Ullah is a dedicated researcher with growing contributions in Fluid Dynamics, where his work reflects strong command in Computational Mathematics, numerical modeling, and complex fluid flow phenomena. His research primarily advances understanding within Fluid Dynamics, including thin film behavior, hybrid nanofluids, nonlinear kinematics, entropy optimization, heat and mass transfer, and numerical schemes applied to Newtonian and non-Newtonian flows. As an active scholar in Fluid Dynamics, he has authored numerous peer-reviewed articles in reputable international journals, addressing contemporary problems in porous media flows, thermal transport, radiative effects, and Machine-Learning-assisted simulation of physical systems. His work in Fluid Dynamics extends to investigations using neural networks, finite-volume computing, and advanced simulation techniques that improve predictive accuracy and enhance engineering applications. Dr. Naeem Ullah consistently collaborates with multidisciplinary researchers across various countries, enriching scientific progress through joint modeling of nanofluid systems and Fluid Dynamics-based thermal processes. His publication record shows steady expansion, demonstrating research depth in entropy-driven transport, convective flow modeling, and Fluid Dynamics mechanisms within geometric and asymmetric flow domains. As a reviewer for high-impact journals, he contributes to scholarly development in Applied Mathematics, Chemical Engineering, and Fluid Dynamics. His research has introduced significant insights regarding Darcy–Forchheimer media, Cattaneo–Christov heat flux, and boundary layer controls, strengthening global understanding of Fluid Dynamics. His academic contributions continue to support industrial, biomedical, energy, and environmental problem-solving through mathematical structure and computational representation of Fluid Dynamics. With a strong professional presence, Dr. Naeem Ullah remains engaged in expanding high-performance algorithms and analytical frameworks in Fluid Dynamics, bridging applied models with real-world heat-mass transfer behavior. His research impact continues to rise with sustained contribution to Fluid Dynamics, advancing predictive solutions, physical simulations, and numerical stability for advanced engineering systems. Google Scholar profile of 144 Citations, 7 h-index, 5 i10-index.

Profile: Google Scholar

Featured Publications

1. Khan, N. S., Shah, Q., Sohail, A., Ullah, Z., Kaewkhao, A., Kumam, P., & Zubair, S., et al. (2021). Rotating flow assessment of magnetized mixture fluid suspended with hybrid nanoparticles and chemical reactions of species. Scientific Reports, 11(1), 11277.

2. Khan, N. S., Usman, A. H., Sohail, A., Hussanan, A., Shah, Q., Ullah, N., & Kumam, P., et al. (2021). A framework for the magnetic dipole effect on the thixotropic nanofluid flow past a continuous curved stretched surface. Crystals, 11(6), 645.

3. Abidin, M. Z., Marwan, M., Ullah, N., & Mohamed Zidan, A. (2023). Well-posedness in variable-exponent function spaces for the three-dimensional micropolar fluid equations. Journal of Mathematics, 2023(1), 4083997.

4. Ibrahim, S., Marwat, D. N. K., Ullah, N., & Nisar, K. S. (2023). Investigation of fluid flow pattern in a 3D meandering tube. Frontiers in Materials, 10, 1187986.

5. Abidin, M. Z., Ullah, N., Hussain, A., Saadaoui, S., Mohamed, M. M. I., & Deifalla, A. (2023). Case study of entropy optimization with the flow of non-Newtonian nanofluid past converging conduit with slip mechanism: An application of geothermal engineering. Case Studies in Thermal Engineering, 52, 103764.

Assoc. Prof. Dr. Osama Hussein Galal | Stochastic Fluid Dynamics | Excellence in Research

Associated Professor | Fayoum University | Egypt

Assoc. Prof. Dr. Osama Hussein Galal is a distinguished academic specializing in Stochastic Fluid Dynamics, whose professional journey reflects exceptional expertise in Engineering Mathematics and Physics. His academic and research trajectory demonstrates profound engagement with Stochastic Fluid Dynamics in analyzing uncertainty quantification, fractional-order systems, and fluid flow modeling. Over his extensive academic tenure, he has served as an educator, researcher, consultant, and supervisor, contributing significantly to Stochastic Fluid Dynamics applications in non-Newtonian fluid analysis, stochastic differential equations, and advanced computational mechanics. His professional experience extends to engineering consultancy and structural design, where he integrated Stochastic Fluid Dynamics methodologies for enhanced prediction accuracy in complex engineering systems. Assoc. Prof. Dr. Osama Hussein Galal has guided numerous postgraduate dissertations focusing on Stochastic Fluid Dynamics and uncertainty modeling in power systems, beam analysis, and transmission lines. His research interest revolves around integrating Stochastic Fluid Dynamics with machine learning, renewable energy modeling, and fractional calculus applications. Recognized for his scholarly contributions, he has received several awards for excellence in teaching, research supervision, and scientific publications. His research skills encompass analytical modeling, stochastic simulation, and the mathematical treatment of Stochastic Fluid Dynamics in engineering contexts, establishing him as a leading voice in the field. Through his numerous publications in reputed international journals, he has advanced global understanding of Stochastic Fluid Dynamics and its engineering implications. His career exemplifies the fusion of theoretical rigor and practical innovation, positioning him as a prominent figure in modern computational and stochastic analysis. Google Scholar profile of 102 Citations, 6 h-index, 5 i10-index.

Featured Publications

1. Hatata, A., Galal, O. H., Said, N., & Ahmed, D. (2021). Prediction of biogas production from anaerobic co-digestion of waste activated sludge and wheat straw using two-dimensional mathematical models and an artificial neural network. Renewable Energy, 178, 226–240.

2. Galal, O. H., El-Tahan, W., El-Tawil, M. A., & Mahmoud, A. A. (2008). Spectral SFEM analysis of structures with stochastic parameters under stochastic excitation. Structural Engineering and Mechanics: An International Journal, 28(3), 281–294.

3. Galal, O. H., El-Tawil, M. A., & Mahmoud, A. A. (2002). Stochastic beam equations under random dynamic loads. International Journal of Solids and Structures, 39(4), 1031–1040.

4. Galal, O. H. (2013). A proposed stochastic finite difference approach based on homogenous chaos expansion. Journal of Applied Mathematics, 2013(1), 950469.

5. El-Beltagy, M. A., Wafa, M. I., & Galal, O. H. (2012). Upwind finite-volume solution of Stochastic Burgers’ equation. Scientific Research Publishing.