September 5, 2017
Machine Learning and Data Science: Research and Applications in Industry
Speaker: Prof. Dr. Katharina Morik, Head of Artificial Intelligence Unit, TU Dortmund University
Prof. Dr. Katharina Morik, head of the artificial intelligence group at TU Dortmund University and speaker of the collaborative research center SFB 876 on machine learning under resource constraints, provides an overview of machine learning and data science research and applications in industry. She describes challenges and approaches for the analysis of very large data sets and high-dimensional data under resource constraints, for example for large and fast data streams and for distributed data. Large fast data streams are for example sensor measurements in the industry for predicting issues in the production process in advance and traffic sensors data streams for predictive traffic planning. Solutions leverage a broad range of methods including statistical learning algorithms like Support Vector Machines (SVM) to graphical models as well as modular and flexible integrated advanced predictive analytics platforms.
Prof. Dr. Katharina Morik
Artificial Intelligence Unit, TU Dortmund University
Prof. Dr. Katharina Morik obtained her PhD from University of Hamburg in 1981 and her habilitation from Technical University of Berlin in 1988. Since 1991 she is professor at TU Dortmund University, where she heads the Artificial Intelligence Unit with a focus on Machine Learning and Data Mining. The broad range of methods includes statistical learning algorithms like Support Vector Machines (SVM) and graphical models. The analysis of very large data sets and high- dimensional data under resource constraints is investigated for data streams and distributed data. She participated in numerous European research projects and coordinated the European project MiningMart (2000 – 2003). Currently she works on the analysis of data streams for traffic planning and smart cities in the European VaVel project. Katharina Morik authored more than 200 publication in recognized journals and conferences. She supports open source software development. Exam- ples of which are the first efficient implementation of a Support Vector Machine, namely SVMlight by Thorsten Joachims, which was started at her AI unit, as well as