Tilburg University, Department of,
Cognitive Science & Artificial Intelligence
5037 AB Tilburg, The Netherlands
Martin Atzmueller is Associate Professor at the Department of Cognitive Science and Artificial Intelligence
at Tilburg University, where he heads the Computational Sensemaking Lab. Furthermore, he is Visiting Professor at the Université Sorbonne Paris Cité.
He earned his habilitation (Dr. habil.) in 2013 at the University of Kassel, where he also was appointed as adjunct professor (Privatdozent). Further, he received his Ph.D. (Dr. rer. nat.) in Computer Science from the University of Würzburg in 2006. He studied Computer Science at the University of Texas at Austin (USA) and at the University of Würzburg where he completed his MSc in Computer Science.
Martin Atzmueller's research interests include Data Science, Artificial Intelligence, Social Sensing, Human Computing and Network Science. His work focuses on how to 'make sense' of complex data and information processes in science and industry by designing and developing approaches, methods and tools for interactive data science and intelligent analytics, leading to computational sensemaking. For instance, this includes the identification of interesting local patterns (e.g., complex structures, exceptional subgroups, and anomalies), predictive modeling, analysis and exploration of complex heterogeneous and multi-modal data, as well as human-machine learning and decision support.
By connecting computational approaches with the human cognitive, behavioral, and social contextual perspectives - thus linking technologies with their users - the goal is to augment human intelligence and to assist human actors in all their purposes, both online and in the physical world.
Lukas Eberhard, Christoph Trattner, and Martin Atzmueller. Predicting Trading Interactions in an Online Marketplace through Location-Based and Online Social Networks. Information Retrieval Journal, 22(2), 2019.
Martin Atzmueller, Benjamin Kloepper, Hassan Al Mawla, Benjamin Jäschke, Martin Hollender, Markus Graube, David Arnu, Andreas Schmidt, Sebastian Heinze, Lukas Schorer, Andreas Kroll, Gerd Stumme, and Leon Urbas. Big Data Analytics for Proactive Industrial Decision Support. atp edition, (58)9 2016.
Christoph Scholz, Martin Atzmueller, Mark Kibanov, and Gerd Stumme. Predictability of Evolving Contacts and Triadic Closure in Human Face-to-Face Proximity Networks. Journal of Social Network Analysis and Mining, (4)217, 2014.
Martin Atzmueller and Thomas Roth-Berghofer. The Mining and Analysis Continuum of Explaining Uncovered. In Research and Development in Intelligent Systems XXVII, Proc. International Conference on Artificial Intelligence (SGAI), 2010.
Martin Atzmueller, Frank Puppe, and Hans-Peter Buscher. Exploiting Background Knowledge for Knowledge-Intensive Subgroup Discovery. In Proc. International Joint Conference on Artificial Intelligence (IJCAI), pages 647–652, Edinburgh, Scotland, 2005.
🔗 Martin Atzmueller, Martin Becker, Mark Kibanov, Christoph Scholz, Stephan Doerfel, Andreas Hotho, Bjoern-Elmar Macek, Folke Mitzlaff, Juergen Mueller, and Gerd Stumme. Ubicon and its Applications for Ubiquitous Social Computing. New Review of Hypermedia and Multimedia, (20)1:53--77, 2014.
🔗Martin Atzmueller and Frank Puppe. Semi-Automatic Visual Subgroup Mining using VIKAMINE. Journal of Universal Computer Science (JUCS), Special Issue on Visual Data Mining, 11 (11), pp. 1752-1765, 2005
WWW 2018: Mining Attributed Networks
DSAA 2017: Mining Attributed Networks
Web Science 2016: Community Detection: From Plain to Attributed Complex Networks
CSSWS 2015: Subgroup and Community Analytics