Explored how stellar surface phenomena influence exoplanet transit depth measurements, using data from Universitat Autònoma de Barcelona and advanced statistical modeling in Python. Built pipelines for data cleaning, feature extraction, and signal-to-noise optimization — workflows that mirror real-world data science tasks.
Four years of computational modeling at KU Leuven and University of Copenhagen, improving legacy Fortran codebases, designing Python-based MCMC calibration models, and streamlining simulation data pipelines. Though unpublished, it deepened my skills in scalable code integration, statistical inference, and clear technical reporting.
Published in Astronomy & Astrophysics, I contributed to building a scalable grid of cloud-free and irradiated model atmospheres. This involved dataset coordination, algorithm tuning, and robust code testing. Read publication
Published in Astronomy & Astrophysics, I contributed to building a scalable 3D grid of equilibrium chemistry models with the software GGchem. Read publication