Short-CV

Michael Grossniklaus is a professor of Computer Science at the University of Konstanz. Since October 2022, he has been part of the Directorate of the Centre for Human | Data | Society. He studied computer science with a focus on databases and information systems at ETH Zürich and graduated with a diploma thesis in context-aware content management in 2001. In 2007, he received a doctorate (thesis: An Object-Oriented Version Model for Context-Aware Content Management). Since 2013 he has been chairing his research group at the University of Konstanz, first as a junior professor and since 2017 as a full professor. He is one of 25 founding Principal Investigators of the Cluster of Excellence “Centre for the Advanced Study of Collective Behaviour”. Since 2022 he has been the Scientific Co-Lead of the Advanced Data and Information Literacy Track, which aims to increase and enhance data and information literacy for students of all disciplines at the University of Konstanz. Michael has expert knowledge in Database Systems, Query Optimization, Graph Databases and Data Streams. He aims to develop innovative database technologies to support novel and emerging application domains. His current research is focused on the design and development of algebraic optimisation techniques for graph databases and data stream processing in the area of event detection techniques.

Research-related publications

• Michael Brendle, Nick Weber, Mahammad Valiyev, Norman May, Robert Schulze, Alexander Böhm, Guido Moerkotte, Michael Grossniklaus: SAHARA: Memory Footprint Reduction of Cloud Databases with Automated Table Partitioning. EDBT 2022: 1:13-1:26. DOI: 10.5441/002/edbt.2022.02
• Leonard Wörteler, Moritz Renftle, Theodoros Chondrogiannis, Michael Grossniklaus: Cardinality Estimation using Label Probability Propagation for Subgraph Matching in Property Graph Databases. EDBT 2022: 2:285-2:297. DOI: 10.48786/edbt.2022.16
• Manuel Hotz, Theodoros Chondrogiannis, Leonard Wörteler, Michael Grossniklaus: Online Landmark-Based Batch Processing of Shortest Path Queries. SSDBM 2021: 133-144. DOI: 10.1145/3468791.3468844
• Florian Wolf, Michael Brendle, Norman May, Paul R. Willems, Kai-Uwe Sattler, Michael Grossniklaus: Robustness Metrics for Relational Query Execution Plans. Proc. VLDB Endow. 11(11): 1360-1372 (2018). DOI: 10.14778/3236187.3236191
• Andreas Weiler, Michael Grossniklaus, Marc H. Scholl: Situation monitoring of urban areas using social media data streams. Inf. Syst. 57: 129-141 (2016). DOI: 10.1016/j.is.2015.09.004
• Andreas Weiler, Michael Grossniklaus, Marc H. Scholl: An evaluation of the run-time and task-based performance of event detection techniques for Twitter. Inf. Syst. 62: 207-219 (2016). DOI: 10.1016/j.is.2016.01.003
• Jürgen Hölsch, Michael Grossniklaus, Marc H. Scholl: Optimization of Nested Queries using the NF² Algebra. SIGMOD Conference 2016: 1765-1780. DOI: 10.1145/2882903.2915241
• Michael Grossniklaus, David Maier, James Miller, Sharmadha Moorthy, Kristin Tufte: Frames: data-driven windows. DEBS 2016: 13-24. DOI: 10.1145/2933267.2933304
• Jürgen Hölsch, Michael Grossniklaus: An Algebra and Equivalences to Transform Graph Patterns in Neo4j. EDBT/ICDT Workshops 2016.
• Lukas Kircher, Michael Grossniklaus, Christian Grün, Marc H. Scholl: Efficient structural bulk updates on the Pre/Dist/Size XML encoding. ICDE 2015: 447-458. DOI: 10.1109/ICDE.2015.7113305
• Michael Brendle, Norman May, Robert Schulze, Alexander Boehm, Guido Moerkotte, Michael Grossniklaus: Design and implementation of data access metrics for automated physical database design. US Patent App. 17/324,896 (2022)
• Norman May, Alexander Boehm, Guido Moerkotte, Michael Brendle, Mahammad Valiyev, Nick Weber, Robert Schulze, Michael Grossniklaus: Workload aware data partitioning. US Patent App. 16/928,951