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Research Groups

  • The Big Data group investigates scalable architectures for the distributed indexing, querying and analysis of large volumes of data. A particular focus is put on information extraction, probabilistic databases and the development of distributed graph- and streaming engines. We thus investigate the whole lifecycle of semantic-data management, beginning with the extraction of entities and relations from textual and semi-structured sources and on to data-cleaning aspects and probabilistic inference. We intensively worked with the Hadoop and Spark platforms for research and teaching in the past, but are also highly interested in developing custom prototypes based on proprietary, asynchronous communication protocols. Contact: Prof. Dr. Martin Theobald
  • The Computational Interaction group conducts research at the intersection of Human-Computer Interaction and Machine Learning, grounded on both foundational and practical principles via computational methods and data-driven models that can enable, support, explain, and improve any kind of user interaction. Contact: Prof. Dr. Luis Leiva
  • Individual and Collective Reasoning is an interdisciplinary research team at the University of Luxembourg which is driven by the insight that intelligent systems (like humans) are characterized not only by their individual reasoning capacity, but also by their social interaction potential. Its overarching goal is to develop and investigate comprehensive formal models and computational realizations of individual and collective reasoning and rationality. Contact: Prof. Dr. Leon van der Torre
  • Knowledge Discovery and Mining is interested in the intersection of Artificial Intelligence, particularly Machine Learning, and Data Science in order to discover novel information in/about data (and understanding its contents). Current research is related to Text Analytics (Topic Identification, Sentiment Analysis, Feature Detection), Artificial Chatbots, and Anomaly Detection. Contact: Prof. Dr. Christoph Schommer
  • The Parallel Computing & Optimisation group conducts research on parallel computing, search and optimization techniques, in particular new research topics include decentralized optimization techniques that nevertheless lead to a good global behavior of the system. The team is specialised in large-scale discrete/combinatorial problems. Contact: Prof. Dr. Pascal Bouvry

 

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