Marc Stieffenhofer

Marc Stieffenhofer is a Postdoctoral Researcher at the Max Planck Institute for Polymer Research (MPG), affiliated with the Organic Electronics group led by Prof. Denis Andrienko. His position is funded by the Collaborative Research Center TRR 146 (Multiscale Simulation Methods for Soft Matter Systems). He holds a Ph.D. from Johannes Gutenberg University Mainz (2022), where he worked under Prof. Kremer on multiscale modeling and deep learning. His research focuses on applying machine learning to enhance molecular dynamics simulations, particularly in evaluating coarse-grained models of organic semiconductors through reverse-mapping techniques.

His academic work includes developing a Python tool for reverse-mapping condensed-phase molecular structures, highlighted in a 2022 publication in Frontiers in Chemistry. This research critiques conventional coarse-grained model assessments by analyzing discrepancies at atomistic resolutions.

Funded by MPG and TRR 146, his current projects bridge computational chemistry and artificial intelligence to improve material simulations. He collaborates with experimental groups to validate models against all-atom reference systems.