Applications of Machine Learning: From Brain-Machine-Interfaces to Autonomous Driving

Machine learning methods have been established in many areas and produce better results for special fields than humans. Current developments like Deep Learning strengthen these trends. This presentation gives a short introduction to the state of the art of Machine Learning and shows a couple of examples where the Department of Computer Engineering, University of Tübingen, especially has its focus on. By means of Brain-Machine-Interfaces good results could be achieved regarding the rehabilitation of stroke patients. Another good example is the Brain-Machine-Interface being tested for adaptive learning systems. More challenges exist in the area of autonomous driving where for example the recognition of the state of the driver plays a key role to check if he or she is able to take back the control of the car in corresponding situations.

Bio

Professor Dr. Wolfgang Rosenstiel studied Informatics at the University of Karlsruhe. There he also received his Diploma in 1980 and his Ph.D. in 1984. From 1986 to 1990 he led the department “Automatization of Integrated Circuit Design” at the Research Center for Information Technology Karlsruhe (FZI Karlsruhe). Since 1990 he is Professor (Chair for Computer Engineering) at the Wilhelm-Schickard-Institute for Informatics at the University of Tübingen. Since 1st October 2010 he is Dean of the Faculty of Science. He was committee member of DFG senate for Collaborative Research Centers. He is editor-in-chief of the Springer journal „Design Automation for Embedded Systems“. He is active in numerous program and executive committees. He is member of GI, IEEE, IFIP 10.5 as well as ITRS-Design-Committee. In 2009 he received an ERC advanced research grant and he is DATE Fellow since 2008. In 2007 he received a Shared University Research Grant from IBM.