Validating explainable AI methods on brain data is key to unlocking deep learning’s full potential in clinical neuroimaging.
Nys Tjade Siegel
Tjade is a dedicated researcher specializing in the application of advanced deep learning models to structural brain MRI data. With a robust background in data science, Tjade focuses on unraveling the complexities of brain age prediction and assessing the efficacy of explainable AI techniques in neuroimaging. Through innovative research, Tjade aims to enhance our understanding of brain health and disease, contributing to the advancement of predictive and interpretable models in the field of clinical neuroimaging.
Validating explainable AI methods on brain data is key to unlocking deep learning’s full potential in clinical neuroimaging.
Present Positions And Title
Research Associate
Research Groups
Email Address
Career
| Period | Institution | Role |
|---|---|---|
| Since 2023 | Charité universitätsmedizin - Berlin | Research associate |
| 2021 | Fraunhofer-Institut für Solare Energiesysteme ISE | Research assistant |
| 2017 - 2020 | Market Logic Software | Working student - data science |
Academic Education
| Year | Degree | Institution | Field of Study |
|---|---|---|---|
| 2023 | M.Sc. | Albert-Ludwigs-Universität Freiburg, Germany | Neuroscience |
| 2020 | B.Sc. | Technische Universität Berlin, Germany | Industrial engineering and management |