Joerg Sander, PhD

Area of Study / Keywords

Computing Science Data Mining Clustering Outlier Detection

About

Education

• M.A., Philosophy of Science, University of Munich, 1989
• Diploma, Computer Science, University of Munich, 1996
• Ph.D., Computer Science, University of Munich, 1998

Research

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.