LEAD Graduate School & Research Network

Tanja Krumpe, M.Sc.

Research Interest

I am working with Brain-Computer Interfaces (BCI) for healthy users, with the aim to develop an application which supports a user in the process of learning by assessing the mental state a user is in and adapting the presented learning material according to this mental state.

I mainly work with EEG to record and analyze brain signals during a cognitive task associated with the process of learning. So far I took an interest in working memory load detection and the executive functions that are associated with the induction of working memory load. Further I am interested in processes and neural correlates associated with memory encoding.

Using BCI for educational purposes is a very interesting field which suits very well in the interdisciplinary structure of LEAD. I am currently working in a close cooperation with the psychology department which has only strengthened due to my associated membership in lead. I hope to find more insightful and fruitful cooperations within the structure of LEAD to profit from the expertise of other faculties and departments that can provide constructive feedback for my work.

Intersection 2: Educational Neuroscience

Supervisors: Prof. Dr. Wolfgang Rosenstiel, Prof. Dr. Peter Gerjets


Curriculum Vitae

since 04/2015 PhD in Computer Science at Departement of Computer Engineering, Group: Neural Interfaces and Brain Signal Decoding
2012-2015 M.Sc. Bioinformatics
2009-2012 B.Sc. Bioinformatics


  • Krumpe, T., Scharinger, C., Gerjets, P., Rosenstiel, W., & Spüler, M. (2018). Unity and diversity in working memory load: Evidence for the separability of the executive functions updating and inhibition using machine learning. Biological Psychology, 139, p.163-172.
  • Krumpe, T., Gerjets, P., Rosenstiel, W., & Spüler, M. (2018). EEG correlates of decision confidence in feedback processing. Proceedings of the 7th International BCI Meeting, p.180-181. Asilomar, CA.
  • Krumpe, T., Baumgärtner, K., Rosenstiel, W., & Spüler, M. (2017). Non-stationarity and inter-subject variability of EEG characteristics in the context of BCI development. Proceedings of the 7th Graz Brain-Computer Interface Conference, p.260-265.
  • Spüler, M., Krumpe, T., Walter, C., Scharinger, C., Rosenstiel, W., & Gerjets, P. (2017). Brain-computer interfaces for educational applications. Informational Environments : Effects of Use, Effective Designs, p.177–201.
  • Grissmann, S., Spüler, M., Faller, J., Krumpe, T., Zander, T., Kelava, A., Scharinger, C., & Gerjets, P. (2017). Context sensitivity of EEG-based workload classification under different affective valence. IEEE Transactions on Affective Computing.
  • Krumpe, T., Walter, C., Rosenstiel, W., & Spüler, M. (2016). Asynchronous P300 classification in a reactive brain-computer interface during an outlier detection task, Journal of Neural Engineering, 13(4). doi:10.1088/1741-2560/13/4/046015
  • Krumpe, T., Scharinger, C., Gerjets, P., Rosenstiel, W., & Spüler, M. (2016). Disentangeling working memory load - finding inhibition and updating components in EEG data. In G.R. Müller-Putz, J. E. Huggins, & E. Steryl (Eds.), Proceedings of the 6th International Brain-Computer Interface Meeting (p. 174). Graz: Verlag der Technischen Universität Graz. doi: 10.3217/978-3-85125-467-9