ScaDS Dresden/Leipzig at CeBIT 2017
Also this year, ScaDS Dresden/Leipzig will continue to present Big Data related research topics at the IT conference and exhibition CeBIT from 20 - 24 March 2017 in Hannover. On the shared booth together with other universities of the Free State of Saxony, Saxony-Anhalt and the Free State of Thuringia we will be part of the TU Dresden exhibit and inform the public in particular about recent developments in Big Data application areas. ScaDS Dresden/Leipzig presentations will be accompanied with other research topics form the Center of Informations Services and High Performance Computing (ZIH) of the TU Dresden, the 5G Lab and the Cluster of Excellence Center for Advancing Electronics Dresden (cfaed).
In particular, ScaDS Dresden/Leipzig and ZIH will inform the interested public about highlights in its research activities, including amongst others:
- Big Data and data intensive computing
- Data analytics and data life cycle management
- High Performance Computing, Distributed and Cloud Computing
- Scalable software tools for application support and energy efficient computing
All visitors and interested attendees of the exhibit are very welcome to visit our boot at Hall 6, Booth B24 in the research and innovation hall of the CeBIT 2017 (see convention center map for further details)
Impressions from the past
In the past we had lively discussions about actual research topics on our booth with visitors of the CeBIT conference and exhibition from media, politics and the general public.
The last year CeBIT 2016 booth team on the shared TU Dresden booth presenting the research activities of ScaDS Dresden/Leipzig, cfaed, 5G Lab and ZIH.
Dr. René Jäkel, management director of ScaDS Dresden/Leipzig, informs EU politician Reinhard Bütikofer about energy efficient computing and service-oriented research in the area of Big Data on CeBIT 2015.
Also on CeBIT 2015 we had prominent visit of our Minister President of the Free State of Saxony Stanislaw Tillich, who was interested in the new area of Big Data research.