Martin Theobald

Prof. Martin Theobald is a Full Professor in Computer Science with a focus on Big Data at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), Department of Computer Science. He leads the Big Data research group and serves as the Study Program Director for the Bachelor in Computer Science (BiCS) program since 2022. Previously, he held professorial roles at the University of Ulm (Co-Director of the Institute for Databases and Information Systems) and the University of Antwerp (Advanced Database Research and Modeling group). His academic journey includes a joint doctoral degree from Saarland University and the Max Planck Institute for Informatics in 2006, followed by a postdoctoral research stint at Stanford University's Infolab from 2006 to 2008.

Education:

• PhD in Computer Science (2006) from Saarland University and Max Planck Institute for Informatics, Saarbrücken
• Postdoctoral Researcher at Stanford University's Infolab (2006–2008)

Research Interests: Martin's work centers on Big Data systems, probabilistic databases, distributed stream processing, and machine learning. He has extensively explored techniques such as asynchronous iterative routing (AIR), real-time neural network training from data streams (TensAIR), and large-scale information extraction leveraging statistical methods. His contributions span scalable architectures, optimization frameworks for deep learning, and knowledge graph construction with high precision and recall.

Publications: His recent work reflects a focus on real-time systems, convergence analysis of distributed algorithms, and robust embedding techniques. Key themes include the development of efficient dataflow engines, probabilistic database models, and frameworks for handling uncertain and temporal data.

Scientific Awards: None explicitly mentioned in the provided texts.

Advising & Grants: Martin has advised numerous students (though names are not listed) and contributed to over 100 international conferences/workshops as a PC member, reviewer, and organizer. He has held editorial roles, including Area Editor for Elsevier’s 'Information Systems' (2013–2018) and PVLDB (2020–2021). His research has driven advancements in Jeopardy! clue-solving SPARQL engines, automotive navigation systems under uncertainty, and the design of open-domain information extraction architectures.

Labs/Teams: Current leadership of the Big Data research group at the University of Luxembourg. Previously led the 'Ranking and Uncertain Data Management' group at the Max Planck Institute for Informatics (2008–2012). Key collaborations include the development of the AIR dataflow engine and the YAGO-QA knowledge base system.