Ole Goltermann

Ole Goltermann

Doctoral Candidate
Research interests: • computational modelling of cognitive processes • explainable artificial intelligence for neuroscience • evolutionary molecular variation affecting structural aspects of brain anatomy • Bayesian learning models of pain • theorization and ontology development in cognitive sciences • why psychology matters

Academic education

since 2021  Doctoral candidate, Max Planck School of Cognition, Leipzig, Germany
                      Lab rotations in the orientation year: Veronica Witte & Arno Villringer, Simon E. Fisher, and Christian Büchel

2019–2021 Master of Science in Psychology (Mind & Brain track), University of Vienna, Austria

2015–2018 Bachelor of Science in Psychology, University of Vienna, Austria

2012–2015 Bachelor of Arts in Business Administration & Dual Study Programme at Robert Bosch GmbH in Germany (Hanover, Stuttgart, & Hildesheim) & Malaysia (Penang)
 

Teaching

2019–2021 Statistical advice on personal website: Free (Donation-based, Sea-Watch e.V.) statistical and methodological advice for bachelor and master theses in psychology

2018–2021 Teaching assistant, Department of Social Psychology, University of Vienna, Austria

2017–2018 Student Advisor, Faculty of Psychology, University of Vienna, Austria

 

Scholarships

2016–2020 Merit-based Scholarship Grant of the Austrian Government
2017–2020 Merit-based Scholarship Grant for Disabled Students, University of Vienna, Austria

 

Poster presentations and talks

Goltermann, O.*, Hofmann, S. M.*, Villringer, A., Witte, A. V., & Beyer, F. (2022). Deep neural networks interpret white matter lesions as a signature of higher-brain-age. Poster presented at Organization for Human Brain Mappin (OHBM) Annual Meeting 2022, Glasgow, Scotland.

Goltermann, O.*, Hofmann, S. M.*, Villringer, A., Witte, A. V., & Beyer, F. (2022). Deep neural networks interpret white matter lesions as a signature of higher-brain-age. Poster presented at 11th IMPRS NeuroCom Summer School, Leipzig, Germany.

Goltermann, O. (2020). Computational modelling of social learning and social influence using ML algorithms of Reinforcement Learning. Talk presented at the Colloquium Series for Social Psychology, University of Hildesheim, Germany.

 

Publication

Hofmann, S. M., Beyer, F., Lapuschkin, S., Goltermann, O., Loeffler, M., Müller, K.-R., Villringer, A., Samek, W., & Witte, A. V. (2021). Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain. Preprint published on bioRxiv.

Büsel, C., Sachse, P., Goltermann, O., & Ansorge, U. (2020). Sense and sensitivity – Using spatial response-compatibility effects to investigate ambiguous word meaning. Experimental Psychology, 67(6), 327–334.

 

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