Joerg Sander, PhD
Area of Study / Keywords
Computing Science Data Mining Clustering Outlier Detection
- M.A., Philosophy of Science, University of Munich, 1989
- Diploma, Computer Science, University of Munich, 1996
- Ph.D., Computer Science, University of Munich, 1998
My research focuses on knowledge discovery in databases, especially clustering and spatial data mining, as well as data management and query processing for non-standard applications. My major research accomplishments include a number of highly cited and influential papers on density-based clustering, unsupervised outlier detection, and spatial data mining. For instance, I has been a main contributor to well-known algorithms for density-based clustering and outlier detection, such as DBSCAN (the DBSCAN paper received in 2014 the first SIGKDD test-of-time award), OPTICS, HDBSCAN*, and LOF, which are covered in several textbooks on data mining, and which have been used in many practical applications.
See my Google Profile for a list of publications.