Hans-Peter Kriegel has been a Professor of Informatics at Ludwig-Maximilians-Universitaet Munich, Germany for over 20 years. He has published over a wide range of data mining topics including clustering, outlier detection and high-dimensional data analysis. In 2009 the Association for Computing Machinery (ACM) elected Professor Kriegel an ACM Fellow for his contributions to knowledge discovery and data mining, similarity search, spatial data management, and access-methods for high-dimensional data. So far, his more than 450 publications have been cited more than 30,000 times according to Google Scholar. Microsoft Academic Search currently ranks him Number 5 for field rating in the field of data mining.
Professor Kriegel's ground-breaking contribution to the data mining field was his paper at the 1996 KDD Conference titled "A density-based algorithm for discovering clusters in large spatial databases with noise" (DBSCAN) with co-authors Martin Ester, Joerg Sander and Xiaowei Xu, with more than 5,000 citations in Google Scholar. That paper led to other density-based approaches such as OPTICS (Ordering Points To Identify the Clustering Structure, SIGMOD 1999) and LOF (Identifying density-based Local Outliers, SIGMOD 2000), both with more than 1,500 citations. His more recent work on clustering as well as on outlier detection in high-dimensional data has led to numerous tutorials at IEEE ICDM and ACM SIGKDD, among other venues. This research has been done together with his team members Peer Kroeger, Erich Schubert and Arthur Zimek.
More recently, Professor Kriegel has been applying some of his work on clustering and outlier detection in interdisciplinary cooperations with other sciences such as archeology, biology, engineering and medical science as well as in industrial collaborations.
2013 IEEE ICDM Nomination and Evaluation Committees