Alkiviades Ch. Payatakes Distinguished Lectures
“Alkiviades Ch. Payatakes” Distinguished Lectures are organised every year by the Institute of Chemical Engineering Sciences of the Foundation for Research and Technology – Hellas (FORTH/ICE-HT), in Patras, to honor the memory of Alkiviades Ch. Payatakes (1945-2009), Professor at the Department of Chemical Engineering, University of Patras, Director of the Institute of Chemical Engineering Sciences of FORTH (1999-2006), and Chairman of FORTH from 2006 until his premature loss, on the 29th November 2009.
On the occasion of the first anniversary of his death, a Symposium to honor the memory of Alkivides Ch. Payatakes was organized by FORTH/ICE-HT and the Department of Chemical Engineering, University of Patras on December 17, 2010. The Symposium included scientific talks by his colleagues, his students and his friends in the areas of Particulate systems; Multiphase flows in porous media; and Transport phenomena in porous media and biological processes, as well as, memorial talks. Participants of the Symposium received an album, entitled “Alkiviades Ch. Payatakes: His life and his work, 1945 – 2009” (in Greek) written by his students. During the Symposium the building of FORTH/ICE-HT which was completed when he was Director of the Institute was named “A. C. Payatakes Building”.
Keynote speakers of the “Alkiviades Ch. Payatakes” Distinguished Lecture series are internationally recognized scientists.
“Alkiviades Ch. Payatakes” Distinguished Lecture 2026
Advances and Challenges in Computational Process Engineering
Andreas G. Boudouvis
Professor, former Rector
National Technical University of Athens
School of Chemical 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.