Get Together - HPC, Big Data, and Machine Learning

by Sunna Torge form TU Dresden

Abstract

The developments in the last years have shown the necessity to bring the research areas HPC, Big Data, and Machine Learning closer together. Often, this was simply driven by the curiosity and visions of researchers. However, it also happened that people are working on related problems, but do not know of each other. In order to support this moving together of the HPC, the Big Data, and the Machine Learning research communities, there are many different initiatives all over the world. In my talk, I want to give you an impression of the activities at the Technical University Dresden in common with the University of Leipzig to push on the interchange between the research areas, enlarge the sight on common research problems, and support the interlocking between methodological and applicational research fields. A selection of ongoing Machine Learning projects are presented, which are undertaken in this scientific environments and benefit from the close integration of the HPC infrastructure, the application science, and the methodolgical expertise.

Slides

About the Speaker

Sunna Torge holds a diploma degree in mathematics (Mathematical Logic) from University of Freiburg and PhD in computer science (Automated Deduction) from University of Munich, where she had a PhD and a Postdoctorial scholarship within the graduate school of Language, Information, and Logic. Sunna Torge has been working in the man-machine interface group at Sony Research (Europe) GmbH and held a professorship for theoretical computer science at the Applied University of Furtwangen. Since 2016 she is a member of the German national competence center for Big Data and Artificial Intelligence “ScaDS.AI” and a Machine Learning teacher at Technical University Dresden.