Dr. rer. nat. Nils R. Winter, M. Sc. 
Postdoc
nils.r.winter@uni-muenster.de
+49 (0)251 83-51847

Projects: FOR2107, MACS, Medical Machine Learning Lab, PHOTONAI

 

 

 

  • CV

    Research Profiles

    Twitter x.com/NilsRWinter
    Open Science Framework osf.io/rcua8
    ORCID id orcid.org/0000-0002-6241-1492
    Research Gate www.researchgate.net/profile/Nils-Winter-2
    Google scholar scholar.google.com/citations
    Personal website www.nilsrwinter.com

    Academic Career

    2023 present Postdoctoral Researcher at Medical Machine Learning Lab, University of Münster
    2019 2023 PhD student at the Otto-Creutzfeldt-Center for Cognitive and Behavioral Neuroscience (OCC), University of Münster, Germany www.uni-muenster.de/OCCMuenster/phd-students/nils-winter.html
    2018 2023 PhD student in psychology (summa cum laude); dissertation title: „Towards Precision Psychiatry – From Univariate to Multivariate Biomarkers of Major Depressive Disorder“ supervised by Prof. Dr. Tim Hahn / Prof. Dr. Dr. Udo Dannlowski / Prof. Dr. Niko Busch at the University of Münster, Germany
    01/2017 12/2017 Research assistant at the Dept. of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt - Goethe University Project: „Genome-based First-line Treatment Response Prediction for Bipolar Disorder“ supervised by Prof. Dr. Tim Hahn and Prof. Dr. Andreas Reif and funded by the LOEWE-Center for Translational Medicine and Pharmacology and the Fraunhofer Institute IME
    10/2014 12/2016 Master of science psychology (specialization in cognitive neuroscience and clinical psychology) at the University of Frankfurt, Germany
    10/2011 09/2014 Bachelor of science psychology at the University of Frankfurt, Germany
    07/2010   A-levels at the Prälat-Diehl-Schule, Groß-Gerau, Germany

    Awards, scholarships, and competitive funds

    2022 Merit Award of the Organization for Human Brain Mapping for an exceptional abstract submitted at the Annual Meeting of the OHBM 2022 in Glasgow, UK
    2019 Congress travel scholarship, DAAD financing the congress participation of the OHBM 2019, Rome, Italy
    2018 Congress travel scholarship, FAZIT financing the congress participation of the OHBM 2018, Singapore, Singapore
    2016 ERASMUS travel stipend financing the research stay at the Centre for Cognitive Neuroimaging, University of Glasgow, UK

  • Research

    Research Interests

    I have a background in psychology with a specialization in cognitive neuroscience and clinical psychology. From an early stage in my academic journey, I developed a fascination with computer science, machine learning and artificial intelligence. As a researcher, I enjoy the interplay between these fields, using statistical modeling and machine learning techniques to explore and address questions related to mental disorders.

    My PhD projects revolves around individualized prediction within the context of precision psychiatry. During my PhD, I focused on two main research directions. Firstly, in collaboration with Ramona Leenings, I undertook the task of programming the machine learning software, photonai, with the aim of making machine learning more accessible to fellow researchers. Secondly, I explored informative biomarkers for major depression. Despite numerous studies attempting to unravel the underlying neurobiological factors of MDD, no biomarker has yet emerged that provides meaningful insights at an individual patient level. Using photonai, I conducted a systematic investigation into univariate and multivariate biomarkers for MDD, shedding light on the current translational roadblock faced by psychiatry and clinical neuroimaging in the discovery of such biomarkers.

    Presently, I am engaged in various projects, including normative modeling, brain age prediction, depressive subtype identification, or canonical correlation analysis. Another particular area of interest for me are theories of mental disorders and network dynamics.

    I am also a PhD student at the Otto-Creutzfeldt-Center for Cognitive and Behavioural Neuroscience (OCC).

    Abroad residence

    01-04/2020 Research stay at the Machine Learning and Neuroimaging Lab, University College of London, UK Project: „Uncovering brain-behavior associations in Major Depressive Disorder using Canonical Correlation Analysis and Partial Least Squares Regression“ supervised by Prof. Dr. Janaina Mourao-Miranda funded by the DAAD
    02-04/2016 Research stay at the Centre for Cognitive Neuroimaging, University of Glasgow, UK Project: „Robust statistics and bayesian estimation for group comparisons in EEG data“ supervised by Dr. Guillaume Rousselet

  • Publications

    Notable publications

    • Winter, N. R., Leenings, R., Ernsting, J., Sarink, K., Fisch, L., Emden, D., ..., T., Dannlowski, U. & Hahn, T. Quantifying Deviations of Brain Structure and Function in Major Depressive Disorder Across Neuroimaging Modalities. JAMA Psychiatry 79, 879–888 (2022).
    • Leenings, R., Winter, N. R., Dannlowski, U. & Hahn, T. Recommendations for machine learning benchmarks in neuroimaging. Neuroimage257, 119298 (2022).
    • Winter, N. R., Cearns, M., Clark, S. R., Leenings, R., Dannlowski, U., Baune, B. T. & Hahn, T. From multivariate methods to an AI ecosystem. Molecular Psychiatry 1–5 (2021). doi:10.1038/s41380-021-01116-y
    • Leenings, R., Winter, N. R., Plagwitz, L., Holstein, V., Ernsting, J., Sarink, K., ..., Dannlowski, U. & Hahn, T. PHOTONAI—A Python API for rapid machine learning model development. Plos One16, e0254062 (2021).
    • Mihalik, A., Chapman, J., Adams, R. A., Winter, N. R., Ferreira, F. S., Shawe-Taylor, J., Mourão-Miranda, J. & Initiative, A. D. N. Canonical Correlation Analysis and Partial Least Squares for identifying brain-behaviour associations: a tutorial and a comparative study. Biological Psychiatry Cognitive Neurosci Neuroimaging (2022). doi:10.1016/j.bpsc.2022.07.012