Green Data Mining: Professor Katharina Morik [Dean's Seminar Series]
- 21 Nov 2019 10:30 am - 21 Dec 2019 11:30 am
- Clayton: 16 Rainforest Walk, Lecture Theatre S3
Caulfield (Video-conferencing): Building E, Level 2, Room 24
- Open to:
- IT research seminars
Speaker: Professor Dr Katharina Morik, TU Dortmund University, Faculty for Computer Science, Artificial Intelligence
In September 2015, the general assembly of the United Nations passed 17 goals for sustainability development that are to be reached until 2030. This is an extension of the millennium development goals declaration from 2000. Since then, data analysis has contributed in several ways to sustainability, particularly in earth and climate science, in sustainable industrial production, and resource-efficient transportation. Also, Machine Learning itself is enhanced to become less resource consuming.
In this talk, after a short overview, two case studies in production will be presented, one detecting anomalies and the other handling many models in real-time. Machine learning can be applied in order to reduce energy and material consumption, but also the energy consumption of Machine Learning itself needs to be reduced. A surprising approach is to use the most complex learning model on ultra-low power devices, the Integer Markov Random Fields.
Katharina Morik received her doctorate from the University of Hamburg in 1981 and her habilitation from the TU Berlin in 1988. In 1991, she established the chair of Artificial Intelligence at the TU Dortmund. Currently, the focus is on Machine Learning algorithms and their theoretically well-based properties, particularly regarding resource consumption. Applications are, for example, in astrophysics, industry 4.0, or traffic infrastructure.
The first efficient implementation of the Support Vector Machine (SVM) and the globally successful data analysis tool RapidMiner were developed at her department. Together with Volker Markl, Katharina Morik heads the working group "Technological Pioneers" of the platform "Learning Systems and Data Science" of the Federal Ministry of Education and Research (BMBF). She was involved in numerous EU projects and has coordinated the MiningMart project.
In 2011, she acquired the Collaborative Research Center SFB 876 "Providing Information by Resource-Constrained Data Analysis", of which she is the spokesperson. It consists of 13 projects and a graduate school for more than 50 Ph D students. She is a spokesperson of the Competence Center for Machine Learning Rhein Ruhr (ML2R) and coordinator of the four German competence centers for machine learning.
She is the author of more than 200 publications in prestigious journals and conferences. She was a member of the editorial board of the journal "Machine Learning" and is currently one of the editors of the international journal "Data Mining and Knowledge Discovery". She was a founding member, Program Chair and Vice Chair of the conference series IEEE International Conference on Data Mining (ICDM) and Program Chair of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Prof. Morik has been a member of the Academy of Technical Sciences since 2015 and of the North Rhine-Westphalian Academy of Sciences and Arts since 2016.
- Marketing, Faculty of IT