Ole Goltermann

Ole Goltermann

Doktorand
Forschungsinteressen: • 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

 

Akademischer Werdegang

seit 2021     Doktorand, Max Planck School of Cognition, Leipzig
                      Promotionsarbeit am Universitätsklinikum Hamburg-Eppendorf
                      Betreuer: Christian Büchel
                      Lab-Rotationen im Orientierungsjahr: Veronica Witte & Arno Villringer, Simon E. Fisher und Christian Büchel

2019–2021 Master of Science in Psychology (Mind & Brain track), Universität Wien, Österreich

2015–2018 Bachelor of Science in Psychology, Universität Wien, Österreich

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

Lehre

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, Universität Wien, Östereich

2017–2018 Student Advisor, Faculty of Psychology, Universität Wien, Östereich

 

Stipendien

2016–2020 Merit-based Scholarship Grant of the Austrian Government
2017–2020 Merit-based Scholarship Grant for Disabled Students, Universität Wien, Östereich

 

Publikationen

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.

 

Posterpräsentationen und Vorträge

Bayramova, R.*, Goltermann, O.*, Enk, L., Hinrichs, M. A. B., Kamp, F., Serio, B., & Hofmann, S. (2022). Explainable AI for higher cognitive functions: How to provide explanations in the face of increasing complexity. Talk given at 22nd Conference of the European Society for Cognitive Psychology, Lille, France.

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. (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.

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.

* geteilte Erstautorenschaft

 

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