Research conducted at the DTAI group focuses on fundamental and applied research in the fields of Declarative Languages, Machine Learning and Knowledge Representation. Within the group there is a subdivision into two subgroups. Each have their own research focus.

Machine Learning Group: The Machine Learning group follows an artificial intelligence approach to the analysis of data. It investigates a wide variety of machine learning, data mining and data analysis problems. It mostly concentrates on problems that involve complex and structured data and background knowledge. It is especially focussing on the use of expressive relational representations, on rich probabilistic models, and on graph- and network analysis. It is applying its techniques in a wide variety of domains such as sports, health and engineering.

Declarative Languages and Systems Group: The DLS group aims at the development of rich declarative languages and solving methods. This includes research on highly expressive formal modeling and specification languages and on the underlying inference techniques needed to solve problems from these specifications, such as querying, satisfiability checking, constraint solving, and optimisation. This also includes the development of novel analysis, solving, execution and compilation technology as well as the exploration of real world applications.

Fundamental Research

Applied Research