Project title: Robust multimodal galaxy embeddings
PI: Chris Lintott
To understand the evolution of galaxies, astronomers study their characteristic features (e.g. 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. This project will research 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.
