Career
His most important contributions are the database index structures R*-tree, X-tree and intelligence quotient-Tree, the cluster analysis algorithms DBSCAN, OPTICS and SUBCLU and the anomaly detection method Local Outlier Factor (LOF). In 2009 the Association for Computing Machinery appointed Hans-Peter Kriegel a "fellow", one of its highest honors. He has been honored in particular for his contributions to "knowledge discovery and data mining, similarity search, spatial data management, and access methods for high-dimensional data".
He was also awarded the 2015 Association for Computing Machinery (ACM) SIGKDD Innovation Award for his contributions to data mining in clustering, outlier detection and high-dimensional data analysis, in particular for density-based approaches.
He is the most cited German researcher in databases and data mining. His current research is focused around correlation clustering, high-dimensional data indexing and analysis, spatial data mining and spatial data management as well as multimedia databases.
His research group publishes a Java software framework titled Environment for DeveLoping KDD-Applications Supported by Index-Structures (ELKI) that is designed for the parallel research of index structures, data mining algorithms and their interaction, such as optimized data mining algorithms based on databases indexes.