Interactive Visual Analytics for Scientific Discovery – Solving Problems with Visual Analytics

  • Daniel Keim | Institute for Computer Science of the University Halle
Speaker Details

Daniel Keim is working in the area of visual database exploration and data mining, as well as similarity search in databases and indexing multimedia databases. In the field of visual data mining, he developed several new techniques which use visualization technology for the purpose of exploring large databases; and he was the chief engineer in designing the VisDB and VisualPoints systems – two visual data exploration system. He has published extensively on visual data exploration, indexing, and data mining, and he has given tutorials on related issues at several large conferences including SIGMOD, VLDB, and KDD. He received his diploma (equivalent to an MS degree) in Computer Science from the University of Dortmund in 1990 and his Ph.D. in Computer Science from the University of Munich in 1994. Currently, he is professor at the Institute for Computer Science of the University Halle, Germany.

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