2026W

• Bachelor Thesis for Computer Science and Business Informatics / 192.143 / PR
• Deep Learning for Natural Language Processing / 192.039 / VU
• Interdisciplinary Project in Data Science / 194.147 / PR
• Seminar for PhD Students / 192.031 / SE

2027S

• Bachelor Thesis for Computer Science and Business Informatics / 192.143 / PR
• Deep Learning for Natural Language Processing / 192.039 / VU
• Seminar for PhD Students / 192.031 / SE
• Seminar in Artificial Intelligence (Neuroscience-based Artificial Intelligence) / 192.047 / SE

• Benchmarking Predictive Coding Networks - Made Simple / Pinchetti, L., Qi, C., Lokshyn, O., Emde, C., M’Charrak, A., Tang, M., Simon, F., Menzat, B. I., Oliviers, G., Bogacz, R., Lukasiewicz, T., & Salvatori, T. (2025). Benchmarking Predictive Coding Networks - Made Simple. In The Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore, April 24-28, 2025. Thirteenth International Conference on Learning Representations (ICLR 2025), Singapore. http://hdl.handle.net/20.500.12708/223683
• Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting / Kayser, M., Menzat, B. I., Emde, C., Bercean, B., Novak, A., Espinosa, A., Papiez, B. W., Gaube, S., Lukasiewicz, T., & Camburu, O.-M. (2024). Fool Me Once? Contrasting Textual and Visual Explanations in a Clinical Decision-Support Setting. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (pp. 18891–18919). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.emnlp-main.1051

• Faithfulness of natural language explanations for vision language model : : an automated test framework / Süss, M. (2026). Faithfulness of natural language explanations for vision language model : : an automated test framework [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.132363
  Download: PDF (1.78 MB)
• Faithful attention attribution in vision transformers for chest X-ray interpretation / Sula, J. (2026). Faithful attention attribution in vision transformers for chest X-ray interpretation [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.132361
  Download: PDF (3.04 MB)

• Outstanding Paper Award
  2024 / Empirical Methods in Natural Language Processing / USA / Website

Soon, this page will include additional information such as reference projects, activities as journal reviewer and editor, memberships in councils and committees, and other research activities.

Until then, please visit Bayar Ilhan Menzat’s research profile in TISS .