Using AI to assess brain health bridges the gap between rapid technology advances and the need for precise care in neurology and psychiatry.
Prof. Dr. Kerstin Ritter
Prof. Dr. Kerstin Ritter is a Full Professor of Machine Learning for Clinical Neuroscience at the University of Tübingen and is a Director at the Hertie Institute for AI in Brain Health. She is PI in the Excellence Cluster “Machine Learning – New Perspectives for Science” and the Tübingen AI Center as well as multiple interdisciplinary research consortia focusing on innovative methods at the intersection of machine learning, statistics and medical applications in neurology and psychiatry. Her research focuses on using advanced AI methods to assess brain health through diverse data types, including neuroimaging, clinical, genetic, and behavioral data. Her contributions to the field have been recognized with awards such as the NARSAD Young Investigator Grant and the Deutsche Multiple Sklerose Gesellschaft Research Prize.
Using AI to assess brain health bridges the gap between rapid technology advances and the need for precise care in neurology and psychiatry.
Present Positions And Title
Professor of Machine Learning for Clinical Neuroscience, Director
Research Groups
Email Address
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Career
Period | Institution | Role |
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Since 2024 | Hertie Institute for AI in Brain Health, University of Tübingen | Professor of Machine Learning, Director |
2018 - 2024 | Department of Psychiatry and Neuroscience, Charité – Universitätsmedizin Berlin | Junior professor of Computational Neuroscience |
2017 - 2024 | Department of Psychiatry and Neuroscience, Charité –Universitätsmedizin Berlin | Group leader of Machine Learning in Clinical Neuroimaging |
2013 - 2017 | Berlin Center for Advanced Neuroimaging, Charité – Universitätsmedizin Berlin | PostDoc |
2008 - 2012 | Bernstein Center for Computational Neuroscience, Berlin | PhD student |
Academic Education
Year | Degree | Institution | Field of Study |
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2021 | Positive interim evaluation of Junior professorship | Charité – Universitätsmedizin Berlin | Machine Learning in Clinical Neuroimaging |
2012 | Dr. rer. nat. | Humboldt-Universität zu Berlin | Computational Neuroscience / Psychology |
2008 | Dipl. Math. | Humboldt-Universität zu Berlin | Mathematics |