In the Department of Machine Learning, we develop models to improve decision making in clinical brain research.
Our team members
Our team combines expertise in machine learning, mathematics, physics, neuroscience and psychology, approaching challenges from diverse angles. We prioritize open access and maintain an open error culture that values sharing and transparency. Our working atmosphere is friendly and conducive to inspiring discussions and mutual appreciation. We are dedicated to supervising bachelor and master students, fostering educational growth. Collaboration is at our core; we work closely with other machine learning experts and clinicians to deepen our understanding and enhance our research outcomes, ensuring that our work is both innovative and impactful.
Leadership
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…
Shreyash Garg
Shreyash is interested in understanding psychiatric disorders by leveraging machine learning methods to integrate data from various modalities. These…
Dr. Sam Gijsen
My work focuses on applying machine learning to advance understanding and prediction in medical neuroscience and psychiatry. To do so, I am…
Marina Lex
Marina is a Ph.D. student in the Department of Psychiatry and Psychotherapy at Charité – Universitätsmedizin Berlin and associated with the Department…
Roshan Rane
Roshan’s Ph.D. research lies at the crossroads of computer science and mental health research. He analyses large population neuroscience databases…
Dr. Marc-André Schulz
With a background in physics, Marc transitioned to machine learning and deep learning, specializing in the development and critical evaluation of…
Moritz Seiler
Moritz Seiler holds a degree in Business Administration (B.Sc.) from the University of Bayreuth and in Statistics (B.Sc.) from the Ludwig Maximilian…
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…
Dr. Didem Stark
Didem Stark is interested in understanding bias and fairness in machine learning models used for clinical neuroimaging data. Using various fairness…
Marija Tochadse
Marija focuses on understanding the factors that contribute to treatment outcome in psychotherapy. For this, she uses structural and functional MRI…