Astrophysicist
How stellar feedback shapes the interstellar medium and drives galaxy evolution — combining multi-wavelength astronomical observations with novel statistical and machine-learning methods
SOFIA in flight at sunset · own photograph
I am a postdoctoral researcher at the Center for Astronomy of Heidelberg University, working with the PHANGS team in the group of Dr. Kathryn Kreckel. My research investigates how stellar feedback shapes the interstellar medium (ISM) and drives galaxy evolution.
I bring together three complementary strengths: multi-wavelength observational expertise (SOFIA/upGREAT, JWST, IRAM 30 m, APEX), a deep understanding of the multi-phase ISM and the role of stellar feedback in regulating its structure and evolution, and a strong track record in astroinformatics, having developed several numerical tools for the interpretation of complex, multi-scale spectral datasets.
As PI of the SOFIA Orion-Legacy program (DLR-funded) and co-I of the SOFIA Legacy Program FEEDBACK, I established a detailed understanding of feedback processes on resolved Galactic scales. As a member of the PHANGS collaboration, I now extend this work to nearby galaxies observed with JWST, bridging the gap between resolved Galactic ISM diagnostics and the statistical study of feedback across diverse galaxy populations.
Massive stars inject energy and momentum into their surroundings through radiation, winds, and supernovae, evacuating cavities and sweeping up dense shells that can both trigger and suppress star formation. Using SOFIA/upGREAT [C II] observations from the FEEDBACK Legacy Program, my group has shown that wind-driven bubbles trigger star formation on timescales as short as ~0.1 Myr while simultaneously dispersing the natal molecular clouds — establishing positive and negative feedback as competing processes. With JWST observations from PHANGS, I now extend this work to entire nearby galaxies, characterising feedback-driven structures across diverse galactic environments.
Molecular clouds form through the interaction of converging atomic streams, leaving residual cold atomic envelopes that surround the newly formed clouds. These envelopes carry substantial mass yet remain largely invisible in emission, betraying their presence through self-absorption in [C II], CO, and H I. To disentangle the multi-phase ISM along the line of sight, I developed an N-layer radiative transfer model that solves spectrally resolved for multiple components simultaneously, recovering the temperature, optical depth, and column density of each layer.
I develop numerical and statistical methods for the analysis of spectral data cubes,
integrated into my open-source Python toolkit astrokit.
The toolkit bundles a growing collection of methods I have built over the years, including
an N-layer radiative transfer model that disentangles the multi-phase ISM along the
line of sight, a Gaussian Mixture Model framework that clusters spectra by shape, and a
procedure to reconstruct the three-dimensional UV radiation field from a stellar census.
Looking ahead, I aim to develop new numerical and statistical techniques tailored to the
data volumes of FYST/CCAT and SKA-era surveys.
Five papers tracing the molecular-cloud lifecycle — from assembly through stellar feedback to dispersal.
My complete list of peer-reviewed publications and ongoing work is maintained on Google Scholar and on the NASA Astrophysics Data System (ADS).







Feel free to reach out about research collaborations, observing proposals, or potential student projects.