Proceedings of the 6th International Conference on Fluid Flow and Thermal Science (ICFFTS 2025)
October 29 - 31, 2025 |Barcelona, Spain
The keynote information for the 6th International Conference on Fluid Flow and Thermal Science (ICFFTS 2025) is as follows:
Plenary Speakers
Dr. Eiyad Abu-Nada
Khalifa University, UAE
Dr. Mostafa S. Shadloo
National Institute of Applied Science (INSA), Rouen and a Researcher at Coria Lab, France
Dr. Eiyad Abu-Nada
Khalifa University, UAE
Prof. Eiyad Abu-Nada is a Full Professor of Mechanical Engineering in the Department of Mechanical Engineering at Khalifa University in Abu Dhabi, UAE. He joined Khalifa University in 2013. Prior to that, he worked as a Full Professor at King Faisal University in Saudi Arabia and Associate Professor at Hashemite University in Jordan. Dr. Abu-Nada is an Alexander von Humboldt Fellow and a recipient of Abdul-Hameed Shoman Award in Jordan. Also, he received the Distinguished Scholar Award from the Arab Fund in Kuwait. His recent research interests are in nanofluid heat transport and microfluidics simulations.
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Dr. Mostafa S. Shadloo
National Institute of Applied Science (INSA), Rouen and a Researcher at Coria Lab, France
Dr. Shadloo is an Associate Professor, since Sept. 2015, at the National Institute of Applied Science (INSA), Rouen and a Researcher at Coria Lab. (CNRS-UMR 6614). Dr. Shadloo is actively engaged in the fields of (i) (aero-) hydrodynamics, turbulence, transitional boundary layers as well as (ii) multiphase, multi-physics fluid flows and heat transfer for the last 15 years. His expertise is mainly in theoretical and computational fluid dynamics (CFD), but has also been active in developing validation strategies and guidelines for CFDist. He aims to develop a new generation high-order coupled algorithm for compressible/incompressible fluid flows with complex physical behaviors, in relation to industrial applications. In this framework, he uses high-performance computing (HPC), high-fidelity direct numerical simulations (DNS) and large-eddy simulations (LES), as well as advance machine learning (ML) techniques to decipher complex instabilities and flow behaviors caused mainly by multi-phase and/or turbulent flows, with heat transfer and compressibility effects.
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