Annotated data is a scarce resource. Unsupervised and self-supervised learning techniques enable researchers to discover structure in unlabelled data sets.
Dr. Sebastian Damrich
Sebastian is a Early Career Research Group Leader at the Hertie AI, where he develops and analyses machine learning models for biomedical data. His focus is on unsupervised and self-supervised methods for representation learning, in particular clustering, dimensionality reduction and visualization, but he has worked on image segmentation as well. With a background in Mathematics, he is also interested geometric deep learning and topological data analysis.
Annotated data is a scarce resource. Unsupervised and self-supervised learning techniques enable researchers to discover structure in unlabelled data sets.