Annotated data is a scarce resource. Unsupervised learning enables researchers to discover structure in unlabelled data sets.
Dr. Sebastian Damrich
Sebastian Damrich is an Early Career Research Group Leader at the Hertie AI, where he develops and analyses machine learning models for neuroscience and 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. He is a member of the ELLIS and the SIAM societies.
Annotated data is a scarce resource. Unsupervised learning enables researchers to discover structure in unlabelled data sets.
Present Positions And Title
Group Leader
Research Group
Email Address
Career
| Period | Institution | Role |
|---|---|---|
| Since 2025 | Hertie Institute for AI in Brain Health, University of Tübingen | Group Leader |
| Since 2023 | Hertie Institute for AI in Brain Health, University of Tübingen | PostDoc |
| 2018 - 2022 | Heidelberg University & University Hospital Heidelberg | PhD Student |
| 2018 | SAP SE | Working Student |
Academic Education
| Year | Degree | Institution | Field of Study |
|---|---|---|---|
| 2022 | PhD | Heidelberg University | Computer Science (interdisciplinary with Mathematics) |
| 2018 | MSc | Heidelberg University | Mathematics |
| 2016 | MASt | University of Cambridge | Mathematics |
| 2015 | BSc | Heidelberg University | Mathematics |