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Kerstin Ritter studied mathematics with minor subjects psychology and philosophy at Westfälische Wilhelms-Universität Münster and Humboldt-Universität zu Berlin (2002-2008). After obtaining a diploma in mathematics (2008), she got a PhD scholarship at the Bernstein Center for Computational Neuroscience and did her PhD in the group of Prof. John-Dylan Haynes about "Decoding multiple sclerosis and related disease parameters using structural brain MRI and multivariate analysis algorithms" (2012). From 2013 to 2015, she was responsible for multimodal data integration within the framework of the EU-funded joint project "Integrative Decision Support System for different types of dementia" (leader: Dr. Ralph Buchert). Since October 2017, she holds a Rahel-Hirsch scholarship and is P.I. in the DFG-funded project “Deep learning for neuroimaging-based disease decoding”. In 2018, she was awarded a NARSAD Young Investigator Grant from the Brain & Behavior Research Foundation (USA) for "Studying mental health via research domain criteria, neuroimaging and convolutional neural networks". Since November 2018, she is a junior professor for Computational Neuroscience at the Department of Psychiatry and Psychotherapy (Charité - Universitätsmedizin Berlin) and leads the research group Machine learning in clinical neuroimaging. Her expertise lies at the intersection of artificial intelligence (machine/deep learning), neuroimaging and neurological/psychiatric diseases (e.g. multiple sclerosis, Alzheimer's disease or depression).