Robert Scholz

Robert Scholz

Doktorand
Forschungsinteressen: • rule acquisition and processing • interactions between cortex and subcortical structures • evolution of brain structures • genetic influence on circuit markup and wiring • deep reinforcement learning

 

Akademischer Werdegang

seit 2020      Doktorand, Max Planck School of Cognition, Leipzig
                       Promotionsarbeit an der Universität Leipzig und an der University of Paris, Frankreich
                       Betreuer: Erich Schröger und  Daniel S. Margulies
                       Lab-Rotationen in der Orientierungsphase: Peter Dayan, Pascal Fries und Daniel S. Margulies

2017–2020  Master of Science in Mind & Brain - Track Brain, Berlin School of Mind & Brain, Humboldt-Universität zu Berlin

2012–2016  Bachelor of Science in Cognitive Sciences, Universität Osnabrück

 

Lehre

2013/2014 Tutor für Artificial Intelligence & Statistics, Universität Osnabrück

 

Publikationen

Machado Costa, K., Scholz, R., Lloyd, K., Moreno-Castilla, P., Gardner, M. P. H., Dayan, P., & Schoenbaum, G. (2022). The role of the lateral orbitofrontal cortex in creating cognitive maps. Nature Neuroscience. https://doi.org/10.1038/s41593-022-01216-0

Scholz, R., Tcholtchev, N., Lämmel, P., & Schieferdecker I. (2018). From metadata catalogs to distributed data processing for smart city platforms and services: A study on the interplay of CKAN and Hadoop. In Ferguson D., Muñoz V., Cardoso J., Helfert M., & Pahl C. (Eds), Cloud computing and service science. CLOSER 2017. Communications in Computer and Information Science, Vol. 864. Springer: Cham. https://doi.org/10.1007/978-3-319-94959-8_7

Scholz, R., Tcholtchev, N., Lämmel, P., & Schieferdecker, I. (2017). A CKAN plugin for data harvesting to the Hadoop distributed file system. In Proceedings of the 7th International Conference on Cloud Computing and Services Science, pp. 47–56. https://doi.org/10.5220/0006230200470056

Schieferdecker, I., Tcholtchev, N., Lämmel, P., Scholz, R., & Lapi, E. (2017). Towards an open data based ICT reference architecture for smart cities. In 2017 International Conference for E-Democracy and Open Government (CeDEM), pp. 184–193. https://doi.org/10.1109./CeDEM.2017.18

Zur Redakteursansicht