Franka Weiler

Information

Bio

I am Franka Weiler, an M.Sc. student in Applied and Engineering Physics at the Technical University of Munich, where I also completed my B.Sc. in Physics. My interests lie at the intersection of physics, machine learning, and Earth observation. During my work at the German Aerospace Center (DLR), I developed a reproducible deep-learning pipeline for estimating cloud base height from stereo all-sky imagery using ceilometer data as reference. What I enjoy most is building methods that are not only technically sound, but also useful in practice.

Current Role

Alongside my master’s studies, I am currently involved in research on simulation-based modelling at TUM. My work focuses on multi-physics problems, especially on connecting different simulation approaches in a consistent and carefully way. This includes the coupling of neutron transport and hydraulic models, as well as work on data exchange and verification workflows.

Areas of Expertise

My main areas of expertise include machine learning for Earth observation, computer vision, remote sensing, and the development of reproducible data and evaluation pipelines. I care particularly about model validation, robustness, and the question of how data-driven methods perform beyond ideal benchmark settings. In the context of ESA Φ-lab CIN, I am especially interested in work that connects innovative machine learning with robust and meaningful Earth observation applications.

Vision for the Future

I believe that even incremental progress matters when it comes to climate change, and that working towards the 2°C target remains both necessary and worthwhile. I hope to contribute to this broader challenge through research in Earth observation that is scientifically robust, practically relevant, and responsive to real environmental needs. In the long term, I would like my work to help deepen our understanding of environmental change and support more sustainable decision-making.

Project as CIN Researcher

Coming Soon