Univ.-Prof. Dr. rer. nat. Tim Hahn
W3 Heisenberg Professor, Medical Machine Learning Lab
hahnt@uni-muenster.de
+49 (0)251 83-56610
CV
Research Profiles
X x.com/therealtimhahn1 ORCID id orcid.org/0000-0001-6541-3795 Research Gate www.researchgate.net/scientific-contributions/Tim-Hahn-2076004778 Google scholar scholar.google.com/citations Academic Career
2019 present W3 Heisenberg Professor for Machine Learning and Predictive Analytics in Psychiatry, Westfälische Wilhelms-Universität Münster, Germany 2017 2019 Group leader Medical Machine Learning Group (Institute for Translational Psychiatry, Westfälische Wilhelms-Universität Münster, Germany 2011 2017 Akademischer Rat at the Department of Cognitive Psychology II, Goethe-Universität Frankfurt, Germany 2010 PhD in Neurobiology, Universität Würzburg, Germany 2007 2010 PhD scholarship of the German Excellence Initiative at the Graduate School of Life Science, Universität Würzburg (with Prof. A. Fallgatter) 2001 2007 Psychology, Philipps-Universität Marburg, Germany Research
Research Interests
Development of biomarkers in the field of mental disorders
High-dimensional pattern recognition (machine learning and modeling)
Neural basis of stable behavioral tendencies
Publications
Notable publications
- Winter NR, Leenings R, Ernsting J, …, Dohm K, …, Leehr EJ, …, Jansen A, Nenadic I, …, Forstner AJ, …, Groß J, …, Kircher T, Dannlowski U*, Hahn T* (*equal contribution). Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder across Neuroimaging Modalities. JAMA Psychiatry 2022;79(9):879-888.
- Hahn T, Ernsting J, Winter NR, …, Kircher T, Risse B, Gaser C, Cole JH, Dannlowski U, Berger K. An uncertainty-aware, shareable and transparent neural network architecture for brain-age modeling. Science Advances 2022;8(1):eabg9471.
- Winter NR, Cearns M, Clark SR, Leenings R, Dannlowski U, Baune BT, Hahn T. From multivariate methods to an AI ecosystem. Molecular Psychiatry 2021; 26(11):6116-6120.
- Flint C, Cearns M, Opel N, Redlich R, Mehler DMA, Emden D, Winter NR, Leenings R, Eickhoff SB, Kircher T, Krug A, Nenadic I, Arolt V, Clark S, Baune BT, Jiang X, Dannlowski U, Hahn T. Systematic misestimation of machine learning performance in neuroimaging studies of depression. Neuropsychopharmacology 2021;46(8):1510-1517.
- Hahn T, Fisch L, Ernsting J, Winter NR, Leenings R, Sarink K, Emden D, Kircher T, Berger K, Dannlowski U. From ‘loose fitting’ to high-performance, uncertainty-aware brain-age modelling. Brain 2021;144(3):e31.