Best Researcher Award
Saleem Nasir
Khalifa University of Science and Technology, United Arab Emirates
Saleem Nasir is a researcher in applied mathematics whose work connects mathematical modelling, computational fluid dynamics, nanofluid mechanics, heat-transfer analysis and computational approaches to engineering problems. He is affiliated with Khalifa University of Science and Technology in Abu Dhabi, where his research has included mathematical and numerical investigations of fluid flow, thermal transport, magnetohydrodynamics and related multiphysics phenomena. His institutional profile identifies research interests including nanofluid mechanics, computational fluid dynamics, mathematical modelling, heat-transfer analysis and artificial neural networks. [1]
Abstract
Saleem Nasir’s research profile is centered on applied mathematical approaches to fluid mechanics and engineering transport phenomena. His work encompasses computational fluid dynamics, nanofluid mechanics, mathematical modelling, heat and mass transfer, magnetohydrodynamic flow and the application of artificial neural networks to nonlinear engineering problems. The institutional record describes his academic background in applied mathematics and identifies research activity spanning analytical, numerical and computational methods. [1] Published studies associated with his profile include investigations of hybrid nanofluids, thermal transport, chemical reactions, electromagnetic effects and intelligent computational modelling. [3] [4] [5]
Keywords
Applied mathematics; computational fluid dynamics; mathematical modelling; nanofluid mechanics; heat transfer; mass transfer; magnetohydrodynamics; nonlinear fluid flow; artificial neural networks; thermal transport; numerical simulation; engineering mathematics.
Introduction
Applied mathematics provides mathematical frameworks for representing, analyzing and solving problems arising in physical sciences and engineering. Within this broad field, computational modelling and numerical simulation are frequently used to examine systems in which analytical solutions are difficult to obtain. Saleem Nasir’s research is positioned at this interface, particularly in the modelling of fluid flow and thermal transport phenomena. His institutional biography identifies fluid dynamics as a major component of his doctoral and subsequent research activity. [1]
Research Profile
According to the institutional profile, Nasir is a Postdoctoral Researcher at Khalifa University of Science and Technology. His academic training includes undergraduate and master’s study in mathematics and a doctoral degree in applied mathematics, with doctoral research focused on fluid dynamics. His research interests include nanofluid mechanics, computational fluid dynamics, mathematical modelling, heat-transfer analysis and artificial neural networks. [1]
Research Contributions
A recurring theme in Nasir’s research is the mathematical and computational analysis of nanofluid flow and thermal behaviour. His published work has examined hybrid and advanced nanofluids under conditions involving chemical reactions, radiation, energy sources and electromagnetic effects. These studies use mathematical formulations and numerical approaches to investigate the coupled behaviour of momentum, temperature and concentration fields. [5] [4]
Publications
Nasir’s publication record includes peer-reviewed studies addressing mathematical modelling, nanofluids, thermal transport, fluid dynamics and computational intelligence. The institutional record lists research outputs associated with Khalifa University, while bibliographic databases provide additional publication and citation information. [1] [2]
- Nasir, S., Berrouk, A. S., and Aamir, A. Modeling nanomaterial transport with chemical reaction and thermal radiation effects using intelligent learning techniques. Journal of Thermal Analysis and Calorimetry, 2026. [3]
Research Impact
Research impact can be considered through multiple complementary dimensions, including scholarly output, citation activity, methodological development and application to engineering problems. The supplied Scopus metrics of 69 documents, 2,383 citations and an h-index of 31 indicate a substantial indexed publication and citation record for the profile presented here. These indicators should be interpreted alongside publication quality, research originality, collaboration and field-specific citation practices. [2] [3] [4]
Award Suitability
The profile demonstrates several characteristics relevant to consideration for a Best Researcher Award. These include an established academic specialization in applied mathematics, an identifiable institutional affiliation, a documented body of peer-reviewed research, and a research program addressing computational and mathematical challenges in fluid and thermal systems. [1][4]
Conclusion
Saleem Nasir’s academic profile reflects a sustained research focus in applied mathematics and its application to fluid mechanics, heat transfer and computational engineering. His work spans mathematical modelling, numerical simulation, nanofluid mechanics, magnetohydrodynamics and artificial-intelligence-assisted analysis. The combination of institutional research activity, peer-reviewed publications and the supplied bibliometric indicators provides a documented basis for considering his profile within a Best Researcher Award framework. [1] [2]
External Links
References
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- Khalifa University of Science and Technology. (n.d.). Dr. Saleem Nasir — Post Doctoral Fellow, Mechanical & Nuclear Engineering. Khalifa University.
https://www.ku.ac.ae/college-people/saleem-nasir
- Scopus. (n.d.). Saleem Nasir — Scopus Research profile. Khalifa University.
https://www.scopus.com/authid/detail.uri?authorId=57194080137
- Nasir, S., Berrouk, A. S., and Gul, T. (2024). Analysis of chemical reactive nanofluid flow on stretching surface using numerical soft computing approach for thermal enhancement. Engineering Applications of Computational Fluid Mechanics, 18(1), 2340609.
https://doi.org/10.1080/19942060.2024.2340609
- Nasir, S., Berrouk, A. S., Gul, T., and Ali, A. (2023). Develop the artificial neural network approach to predict thermal transport analysis of nanofluid inside a porous enclosure. Scientific Reports, 13, 21039.
https://doi.org/10.1038/s41598-023-48412-x
- Nasir, S., Berrouk, A. S., and collaborators. (2023). Numerical and intelligent neuro-computational modelling with Fourier’s energy and Fick’s mass flux theory of 3D fluid flow through a stretchable surface.
https://doi.org/10.1080/19942060.2023.2270675