Andreas G. Boudouvis is a Professor of Chemical Engineering and served as Rector of the National Technical University of Athens (NTUA) from 2019 to 2023. He was Dean of the School of Chemical Engineering (2013–2016) and Director of the interdisciplinary Postgraduate Programme in Computational Mechanics at NTUA (201–2026). He holds a Diploma in Chemical Engineering from NTUA and a Ph.D. from the University of Minnesota (USA). He has served as a Visiting Professor and Researcher at Université de Lorraine (France), Fondation STAE (France), and Johns Hopkins University (USA). He served as Co-President of the European University Alliance EULiST (2021–2023) and is currently a member of its Advisory Council. He has taught undergraduate and postgraduate courses in Transport Phenomena and Computational Methods. His research focuses on the computational analysis of transport phenomena, multiscale modeling, model order reduction, machine learning, and large-scale scientific computing. In 2024, he received the Excellence in University Teaching Award from the Foundation for Research and Technology – Hellas (FORTH).
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Curriculum Vitae of Professor Andreas G. Boudouvis
Also, find below the title and abstract of the proposed talk. The abstract provides a brief overview of the topic to be discussed.
Advances and Challenges in Computational Process Engineering
Abstract
Predicting and controlling product characteristics across spatial scales, from the macroscopic down to the nanoscale, which determine product properties and applications, requires linking these characteristics to the macroscopic parameters and operating conditions of the manufacturing process. Establishing this link calls for multiscale analysis, the development and coupling of computational methods operating at different spatial scales, and computationally intensive simulations. Current advances and challenges concern both the scope and computational efficiency of these methods, as well as the potential for integrating reduced-order models with data-driven machine learning approaches. Applications to chemical vapor deposition processes will be presented.