Generative models can help us understand and explore the main factors of variation in medical images.
Sarah Müller
Sarah is a Ph.D. student in the Department of Data Science at the Hertie Institute for AI in Brain Health at the University of Tübingen, an IMPRS-IS scholar, and part of the Cluster of Excellence project "Uncovering the inner structure of medical images through generative modeling". In her work, she aims to investigate the image generation process of medical images to model variation among patient populations and disease developments. Her research interests include representation learning, generative models, and disentanglement.
Generative models can help us understand and explore the main factors of variation in medical images.
Present Positions And Title
PhD Student
Research Group
Email Address
Phone
Career
| Period | Institution | Role |
|---|---|---|
| Since 2021 | University of Tübingen | PhD Student |
| 2020 | University of Stuttgart | Teaching Assistant for Signal Processing |
| 2019 | Daimler AG, R&D | Internship, Deep Learning and Software Development |
| 2018 - 2020 | University of Stuttgart | Teaching Assistant for Control Engineering |
| 2018 - 2020 | University Hospital Tübingen | Research Assistant for Medical Imaging |
| 2017 - 2018 | University of Stuttgart | Teaching Assistant for Mathematics |
Academic Education
| Year | Degree | Institution | Field of Study |
|---|---|---|---|
| 2018 - 2021 | M.Sc. | University of Stuttgart | Engineering Cybernetics |
| 2014 - 2018 | B.Sc. | University of Tübingen and University of Stuttgart | Medical Engineering |