Biography
Sophia is an incoming PhD student in the Sustainable Machine Learning group at the Machine Learning Section, Department of Computer Science, University of Copenhagen (UCPH).
She holds a master’s degree in Computational Physics and a bachelor’s degree in Physics, both from the Niels Bohr Institute, UCPH.
Her research focuses on resource-efficient and physics-informed machine learning.
Sophia also has a background in astrophysics, with research focusing on estimating hydrogen gas masses in high-redshift galaxies and measuring cosmological parameters using fast radio bursts.
News
2025-05
Submitted my master's thesis on reducing the carbon footprint of machine learning with physics-informed techniques.
2025-03
Presented my research at the 4th Annual Niels Bohr Institute MSc Student Symposium.
2024-10
Participated in the AI Structured Learning 2024 Workshop in Göteborg.
2024-08
Attended the Hamlet-Physics 2024 Conference in Copenhagen.
2024-06
Completed an exchange semester at the University of Amsterdam, focusing on machine learning and astrophysics.
2023-05
Published my first-author paper in Astronomy & Astrophysics on calibrating far-infrared oxygen emission lines to estimate hydrogen gas masses in high-redshift galaxies.
2022-08
Attended the Astromatic Summer School at the University of Montreal.
2022-06
Defended my bachelor’s thesis on measuring cosmological parameters with fast radio bursts.
2022-05
Participated in the Annual Danish Astronomy Meeting in Middelfart.
2021-08
Attended the Nordic Optical Telescope Summer School in Las Palmas.