Research Areas

The Research Vision of Reinhard Maurer is to develop and apply new simulation methods and prediction tools that fuse machine learning (ML) and data-driven approaches with quantum mechanical (QM) electronic structure and dynamical simulation methods. Doing so will remove existing bottlenecks in simulation capabilities that limit the length and time scales and the complexity of chemical simulations. More importantly, hybrid ML/QM methods enable fundamentally new prediction approaches that defy the conventional structure-to-property paradigm that underpins modern chemical studies. The Maurer group applies newly developed ML-enabled research tools in the areas of high-throughput molecular design for organic electronics and functional interfaces, as well as the study of chemical dynamics triggered by extremely short or intense light and electromagnetic fields.

The research of Georg Kresse focuses on the development of advanced first-principles methods for electronic-structure calculations, including approaches that go beyond density functional theory. A cornerstone of the group’s work is the Vienna Ab initio Simulation Package (VASP), which enables highly accurate simulations of materials properties from fundamental quantum mechanics.

Currently, his research focus has shifted toward bringing the precision of high-level quantum chemistry and many-body theory to real materials. By integrating on-the-fly machine learning with auxiliary field quantum Monte Carlo methods, his group seeks to bridge the gap between approximate density functionals and exact theory. This work includes developing surrogate models for complex systems and exploring many-body perturbation techniques to predict electronic and optical properties with unprecedented accuracy. As a founding member of the MECS Cluster of Excellence, he also remains dedicated to advancing the materials modeling necessary to address the global energy crisis.