Daniela Huppenkothen

Daniela Huppenkothen is an Assistant Professor at the Anton Pannekoek Institute for Astronomy at the University of Amsterdam, where she does research at the interface of astronomy and data science. She is particularly interested in how modern statistical tools and machine learning methods to learn about the universe can be used. With her group of students and with collaborators, she currently works on a diverse range of topics, including unsupervised learning of Fast Radio Burst time series, simulation-based inference and neural network emulators for complex astrophysical models of high-energy phenomena, machine learning and causal inference in exoplanet demographics, and machine learning models of systematic effects in X-ray telescopes.Her research aligns closely with SMASH’s Research Area 1 “Data Science — Machine Learning for Scientific Applications”. 

The Anton Pannekoek Institute for Astronomy (API) is an astronomy department with ~20 faculty, and ~100 researchers and students total. Research spans a wide range of astrophysical topics including exoplanets and protoplanetary disks, radio transients, magnetohydrodynamic simulations, astrochemistry, and compact objects. There are numerous ongoing projects within the institute—many with my involvement—that actively incorporate data science and machine learning into research projects.