MPI Colloquia Series | 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.

About the speaker (Personal website)

Alexander Mitsos Ph.D. has been a university professor of systems engineering at the Faculty of Mechanical Engineering at RWTH Aachen University since September 2012. His research focuses on the optimal development and management of chemical processes and energy systems on the one hand, and theory and algorithms for deterministic global optimisation on the other.