Berlin Big Data Center (Phase 2)
Duration: October 2018 – September 2021
Funded by Federal Ministry of Education and Research (BMBF)
The Berlin Big Data Center (BBDC) was established in October 2014 to organize and intelligently process vast amounts of data through the merger of two fields: data management and machine learning. In addition, the BBDC explored data analysis languages/systems and scalable methods of machine learning with a focus on materials research, medicine, and information marketplaces. To highlight Big Data research in Berlin and to encourage networking and collaboration, the BBDC showroom was created.
For BBDC (Phase 2), the scalability of data (related to the number and diversity of data sources) and real-time processing of continuous data streams is explored. This requires a combination of signal processing, statistical, machine learning, and artificial intelligence applications.
TU Berlin, TUBS, ZIB, Charité, Beuth University of Applied Sciences Berlin, and DFKI; associate project partners: Polytechnic University of Milan, École Polytechnique Université Paris-Sarclay, University of Tokyo and National Institute of Informatics, TU Darmstadt, University College London, Fritz Haber Institute of the Max Planck Society, University of Luxembourg, University of Basel, University of California—Irvine, and University of Tokyo and RIKEN AI Center.
Gül, S., Meyer, J., Hellge, C., Schierl, T., Samek, W. (2016). Hybrid video object tracking in H.265/HEVC video streams. International Workshop on Multimedia Signal Processing (MMSP), 1–5.
Srinivasan, V., Lapuschkin, S., Hellge, C., Müller, K.-R., Samek, W. (2017). Interpretable human action recognition in compressed domain. IEEE ICASSP, 1692–1696.
Pronobis, W., Panknin, D., Kirschnick, J., Srinivasan, V., Samek, W., Markl, V., Kaul, M., Müller, K.-R., Nakajima, S. (2018). Sharing hash codes for multiple purposes. Japanese Journal of Statistics and Data Science, 1(1): 215–246.