TU Wien Informatics


Our research aims at enabling machines to mimic human-like intelligence, via models and algorithms to process vast amounts of data, recognize patterns, and make decisions, using techniques from machine and deep learning as well as symbolic reasoning.

In our research activities, we cover all modalities, including natural language processing and computer vision. We focus especially on (i) explainable AI, (ii) deep learning with logical constraints for safe AI , (iii) hybrid model-based approaches to explainable, fair, and robust AI, (iv) general AI via predictive coding and active inference, and (v) intelligent applications, such as in healthcare and law.

The research Unit Artificial Intelligence Techniques is part of the Institute of Logic and Computation.

Thomas Lukasiewicz
Thomas Lukasiewicz T. Lukasiewicz

Head of Research Unit
Univ.Prof. Dipl.-Inf. Dr.

Bayar Ilhan Menzat
Bayar Ilhan Menzat B. Menzat

PostDoc Researcher

  • Deep learning für das Semantic Web / Hohenecker, P. (2016). Deep learning für das Semantic Web [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2016.37489
    Download: PDF (1.11 MB)

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Until then, please visit Artificial Intelligence Techniques’ research profile in TISS .