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.

     

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