Research
The Keefer group’s general paradigm is to theoretically design and predict novel means to measure and manipulate molecular motion with light.
Artificial Intelligence
We develop new ways to leverage machine learning tools for excited state molecular dynamics and ultrafast spectroscopy. Artificial intelligence to us is a tremendously useful numerical tool that can help us to generate new chemical and physical insight. Our first aim is to speed up and streamline otherwise tedious numerical procedures, enabling new simulation regimes. Our second aim is to uncover correlations between high-dimensional molecular and spectroscopic data sets and molecular functionality.
Key achievements
| Substantially improved accuray in the generation of conical intersection topographies and non-adiabatic couplings for molecular quantum dynamics | P. Idzko, ..., DK*, in preparation (2026) |
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