My research focuses on enabling technologies for "intelligent embedded systems" and how many such systems can best work together to create robust and efficient "systems of intelligent systems".
In my research, I develop enabling technologies for "intelligent embedded systems" and how a multitude of such systems can best work together to create robust and efficient "systems of intelligent systems". In these systems, intelligence (i.e., artificial intelligence and machine learning) has been moved from central data centers and the cloud to the end nodes of the internet (i.e., edge computing and intelligent embedded systems). My research includes adapting the machine learning models to the computational capacity that is available in today's and the future's embedded systems, and how we can create a collaborative / federated learning between distributed nodes. I am also researching how to adapt the computer architectures for embedded systems, so that they can better perform the calculations that machine learning requires.
I teach the course "Deep Learning - methods and applications" which is given twice a year; and the course “Student Conference in Electronics and Mechatronics and Current Topic in Interaction Technology and Design”.