AI Enabled Probes of Large Astronomical Surveys
Welcome!
I work on finding ways to analyse our large survey science data in new and efficient ways to make the most of what we are collecting! I investigate modern AI methods and their properties to enable new science probes from the large data products observatories are collecting!
I am a Schmidt AI in Science Fellow funded through Schmidt Sciences, and an Associate Research Fellow at Reuben College.
Schmidt AI in Science Fellowship
Robust multimodal galaxy embeddings
To understand the evolution of galaxies, astronomers study their characteristic features (eg spiral arms). Machine learning has been used successfully to retrieve certain properties from millions of galaxies! To retrieve other properties, new models must be trained which can be costly and time-consuming. I am researching the application of a new class of AI models trained on different observations of the same objects, giving the resulting model the ability to identify a broader range of characteristics, and potentially uncover new physics.