MPI Kolloquiumsreihe | Prof. Alexander Mitsos, RWTH Aachen

The Max Planck Institute Magdeburg invites you to its series of colloquia.
Top-class scientists, from notable German and worldwide research institutions, give a survey of their research work.

Everybody who is interested, is invited to attend.

Abstract

This talk gives an overview of our work in developing and using machine learning techniques for chemical engineering. We first briefly discuss how deterministic global optimization with neural networks embedded can be made tractable by reduced space formulation. We then present our work on property prediction with graph neural networks, including the usage of thermodynamic consistent models. We use these predictions for the computer-aided molecular design with generative machine learning. Finally, we discuss hardware-in-the-loop optimization using inline reaction monitoring.

Über den Sprecher (Personal website)

Alexander Mitsos Ph.D. ist seit September 2012 Universitätsprofessor für das Fach Systemverfahrenstechnik der Fakultät für Maschinenwesen der RWTH Aachen University. Seine Forschungsschwerpunkte sind einerseits optimale Entwicklung und Führung von chemischen Prozessen und Energiesystemen, und andererseits Theorie und Algorithmen für deterministische globale Optimierung.