Katharina Morik
Full professor for computer science and artificial intelligence
Artificial Intelligence Unit, TU Dortmund University, Dortmund, Germany
Katharina Morik is full professor for computer science at the TU Dortmund University, Germany. She earned her Ph.D. (1981) at the University of Hamburg and her habilitation (1988) at the TU Berlin. Starting with natural language processing, her interest moved to Machine Learning ranging from inductive logic programming to statistical learning, then to the analysis of very large data collections, high-dimensional data, and resource awareness. She is a member of the National Academy of Science and Engineering and the North-Rhine-Westphalia Academy of Science and Art. She is the author of more than 200 papers in well acknowledged conferences and journals. Her latest results include spatio-temporal random fields and integer Markov random fields, both allowing for complex graphical models under resource constraints. Her aim to share scientific results strongly supports open source developments. For instance, the first efficient implementation of the support vector machine, SVM_light,, was developed at her lab by Thorsten Joachims. Also the leading data mining platform RapidMiner started out at her lab, which continues to contribute to it. Currently, the Java streams framework is developed, which abstracts processes on distributed data streams. Since 2011, she is leading the collaborative research center SFB 876 on resource-aware data analysis, an interdisciplinary center comprising 14 projects, 20 professors, and about 50 PhD students or Postdocs. She was one of those starting the IEEE International Conference on Data Mining together with Xindong Wu, and was chairing the program of this conference in 2004. She was the program chair of the European Conference on Machine Learning (ECML) in 1989 and one of the program chairs of ECML PKDD 2008. She is in the editorial boards of the international journals “Knowledge and Information Systems” and “Data Mining and Knowledge Discovery”.