I am a Data Scientist working at Heidelberg Materials. I deliver machine learning models to increase the efficiency of production in cement plants and contribute to Python infrastructure in the Digital department.

I have worked as a Doctoral Researcher at Max Planck Insitute for Astronomy (MPIA) in cooperation with Heidelberg University. I developed physical models, reduceed the observational data, and used machine learning to accelerate the data modeling. I collaborated with colleagues and lead my own scientific projects. I organized the group meeting. I also worked on updating legacy scientific codes, creating Python interfaces for them, and/or deploy them on SLURM/MPI computing clusters.

As a researcher, I worked on protoplanetary disk physical and chemical structure modeling, and on fitting these models to (sub-)mm interferometric observations, using Bayesian analysis and machine learning.