Adrem Data Lab focuses on foundational research in the areas of databases, knowledge management, and data mining. Our topics of interest include:

  • Scalable data-mining and knowledge discovery principles and algorithms, for the unsupervised detection of patterns in the form of statistical correlations and logical dependencies, and the supervised learning of models for classification
  • Deterministic and probabilistic data-cleaning techniques in the presence of logical constraints and data uncertainty
  • Development and application of data mining strategies for the integrative analysis and interpretation of heterogeneous biomolecular (proteome, metabolome, genome, …) profiles, structures, spectra and networks
  • Practical application and research on algorithms and methodologies for recommender systems
  • Anomaly detection in the context of process mining
  • Techniques for improving the performance of queries on probabilistic databases
  • Centralized and distributed database architectures for the scalable support of structured, semi-structured, and graph-oriented data models
  • Inductive databases and query languages, towards the goal of integrating data mining technologies in database systems
  • Formal query languages, including the development of efficient processing and query-optimization techniques

Are you interested in a post-doctoral research position in the ADReM research group? Then contact one of the members of staff for more information.