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Andreas Boudouvis

Prof. Andreas Boudouvis

School of Chemical Engineering, National Technical University of Athens, Zografo...

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Prof. Dr. Andreas G. Boudouvis is a Professor at the National Technical University of Athens (NTUA), School of Chemical Engineering (ChES). He was Rector of NTUA, 2019–2023, and Dean of ChES, 2013–2016. He completed his Diploma studies in Chemical Engineering at NTUA, Greece in 1982 and PhD studies in Chemical Engineering and Materials Science at the University of Minnesota, Minneapolis, MN, USA in 1987. He has been awarded the Excellence in Academic Teaching Award, by the Foundation for Research and Technology-Hellas (FORTH) in 2024 in memory of V. Xanthopoulos and S. Pnevmatikos . His teaching disciplines include Fluid Mechanics, Computational Transport Phenomena, Computer Programming, and his research interests include Transport Phenomena, Interfacial Phenomena, Magneto-Electro-Fluid Mechanics, Nonlinear Phenomena, Large-Scale Scientific Computing, Multiscale Analysis, and Reduced-Order Modeling/Machine Learning.

Research Keywords & Expertise

Transport Phenomena
Interfacial phenomena
nonlinear phenomena
Magneto-Electro-Fluid ...
Large-Scale Scientific...

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Transport Phenomena

Short Biography

Prof. Dr. Andreas G. Boudouvis is a Professor at the National Technical University of Athens (NTUA), School of Chemical Engineering (ChES). He was Rector of NTUA, 2019–2023, and Dean of ChES, 2013–2016. He completed his Diploma studies in Chemical Engineering at NTUA, Greece in 1982 and PhD studies in Chemical Engineering and Materials Science at the University of Minnesota, Minneapolis, MN, USA in 1987. He has been awarded the Excellence in Academic Teaching Award, by the Foundation for Research and Technology-Hellas (FORTH) in 2024 in memory of V. Xanthopoulos and S. Pnevmatikos . His teaching disciplines include Fluid Mechanics, Computational Transport Phenomena, Computer Programming, and his research interests include Transport Phenomena, Interfacial Phenomena, Magneto-Electro-Fluid Mechanics, Nonlinear Phenomena, Large-Scale Scientific Computing, Multiscale Analysis, and Reduced-Order Modeling/Machine Learning.