Short Bio

I am an SAO postdoctoral fellow in Catherine Zucker's group, where I am working on constructing the first self-consistent, all-sky 3D census of young stars in the solar neighborhood. This map aims to better constrain the physics of the galactic baryon cycle in a highly resolved volume of the local Milky Way and shed more light on how molecular clouds convert gas into stars, and how feedback from those stars shapes their surrounding environments and regulates subsequent star formation. I am applying modern machine learning methods to integrate data from multiple surveys to infer probabilistic ages and distances, even for stars with incomplete observations.

Formerly, I was an FFG funded postdoc at the Data Science Research Network at the University of Vienna where my goal was to provide a detailed overview of nearby young star clusters and to study the star formation history and build-up of the Scorpius-Centaurus OB association. Our catalog serves as a foundation for future research on critical astrophysical questions, such as the initial mass function, local gas star formation rate, and timescales for star and planet formation.

During my PhD at the Data Science Research Network in Vienna, I have worked with João Alves, Torsten Möller, and Immanuel Bomze to develop tailored machine-learning techniques to identify and characterize stellar clusters in nearby regions of the Milky Way.