Dr. Jaimon Dennis Quadros | Computational Methods | Best Researcher Award

Dr. Jaimon Dennis Quadros | Computational Methods | Best Researcher Award

Lecturer | School of Engineering and Built Environment, University of Greater Manchester | United Kingdom

Dr. Jaimon Dennis Quadros is a distinguished researcher recognized for advanced contributions in Computational Methods applied to mechanical engineering and fluid sciences. His expertise centers on Computational Methods for fluid dynamics, heat transfer, multiphase flows, and intelligent optimization, with strong emphasis on Computational Methods integrated with artificial intelligence, neural networks, and machine learning. Dr. Jaimon Dennis Quadros has produced an extensive body of scholarly work, authoring more than seventy peer reviewed publications that highlight the effectiveness of Computational Methods in predicting complex physical phenomena. His research demonstrates how Computational Methods enhance accuracy, efficiency, and reliability in engineering analysis and design. Through international academic and industry collaborations, he has successfully applied Computational Methods to aerospace, automotive, manufacturing, and thermal systems, supporting innovation and sustainable engineering solutions. His mentorship and leadership have strengthened research capacity and knowledge transfer across institutions. The societal impact of his work lies in advancing safer designs, improved energy efficiency, and data informed decision making through Computational Methods. Scopus profile of 198 Citations, 35 Documents, 8 h index.

Citation Metrics (Scopus)

198
150
100
50
0

Citations

198

Documents

35

h-index

8

Citations

Documents

h-index

Featured Publications

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

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.

Profiles: Google Scholar | ORCID

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.