Clinical neuroscience will benefit from deep learning's versatility rather than from raw scale and compute.
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 particularly interested in multimodal modeling to leverage diverse sources of information. Furthermore, I love to explore the novel options deep learning provides, both by enabling novel data fusion and unsupervised pretraining techniques. Besides helping us to generate scientific insight, I hope we can leverage machine learning to make considerably progress towards practical clinical applications.
Clinical neuroscience will benefit from deep learning's versatility rather than from raw scale and compute.
Present Positions And Title
PostDoc
Research Groups
Email Address
Career
Period | Institution | Role |
---|---|---|
Since 2023 | Department of Psychiatry and Neuroscience, Charité - Universitätsmedizin Berlin, Germany | PostDoc |
2017 - 2018 | Department of Neuroimaging, King's College London, United Kingdom | Research Assistant |
Academic Education
Year | Degree | Institution | Field of Study |
---|---|---|---|
2018 - 2022 | PhD | Freie Universität Berlin, Germany | Computational cognitive neuroscience |
2015 - 2017 | M.Sc. | Maastricht University, Netherlands | Neuroscience |
2012 - 2015 | B.Sc. | Maastricht University, Netherlands | Psychology |