The Data Management and Knowledge-Driven AI (DMKI) Lab is part of the Databases and Artificial Intelligence (DBAI) group at TU Wien's Institute of Logic and Computation within the Faculty of Informatics.
Our research lies at the intersection of data management, knowledge graphs, and artificial intelligence, with a strong emphasis on scalable, reliable, and semantics-aware methods.
We investigate how large, heterogeneous, and complex data can be transformed into structured knowledge and effectively combined with modern AI techniques, such as large language models, to design and build intelligent systems. A central goal of our work is to enable meaningful, trustworthy, and reusable data-driven systems, with a particular focus on healthcare, bioscience, and data-intensive analytics, while maintaining strong theoretical foundations and real-world impact.
We are currently looking for new team members: 2 postdocs!
More details here.
Full Title: From Structures to Vectors: Decoding How Knowledge Graph Characteristics Shape Embedding Strategies
Funding: WWTF (Vienna Science And Technology Fund)
Full Title: Natural Language Access and Performance Boost for TUInsight
Funding: TU Wien
Full Title: Data Engineering and Artificial Intelligence
Funding: Erasmus Mundus Joint Master
Full Title: Reliable Conversational Domain-specific Data Exploration and Analysis
Funding: Horizon Europe MSCA DN (Grant Agreement No. 101168951)
Full Title: Health Virtual Twins for the Personalised Management of Stroke Related to Atrial Fibrillation
Funding: Horizon Europe (Grant Agreement No. 101136244)
Full Title: Applying Artificial Intelligence to Define Clinical Trajectories for Personalized Prediction and Early Detection of Comorbidity and Multimorbidity Patterns
Funding: Horizon Europe (Grant Agreement No. 101080189)
Full Title: Global Network on Large-Scale, Cross-domain and Multilingual Open Knowledge Graphs (GOBLIN)
Funding: COST (European Cooperation in Science and Technology) (CA23147)
Full Title: Knowledge Graphs in the Era of Large Language Models (KGELL)
Funding: COST (European Cooperation in Science and Technology) (CA24121)
