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Matthias Kricke

Matthias Kricke


ScaDS

About

  • Since 08/2016: Researcher at Big Data Competence Center (ScaDS Dresden/Leipzig)
  • 03/2014 - 07/2016: IT-Specialist, mgm technology partners GmbH
    • BigData Projects with BMW Forschung und Technik GmbH, GfK Data & Technology, Lidl
  • 08/2012 - 02/2014: Algorithm Engineer at R&D of Unister GmbH

  • Master of Science (Computer Science), MLU Halle-Wittenberg, November 2012

Contact

  • +49 341 97 39-517
  • kricke [at] informatik.uni-leipzig.de
  • Ritterstraße 9, ScaDS 2. Etage, Room 2.4

Research Interests

  • Graph-based Data Integration & Matching
  • Big Data Frameworks
    • Distributed Computation Frameworks (Flink, Spark, etc.)
    • Distributed Storage Systems (Accumulo, HBase, etc.)
    • Geotempoal Data Management (Geomesa, Geowave, Timly etc.)
    • (new )Time-Series-Data Management

Talks

Publications


further information
Google Scholar
Matthias Kricke; Martin Grimmer; Michael Schmeißer
Preserving Recomputability of Results from Big Data Transformation Workflows Depending on External Systems and Human Interaction
Datenbank-Spektrum
2017-09

further information
Google Scholar
Pascal Hirmer; Tim Waizenegger; Ghareeb Falazi; Majd Abdo; Yuliya Volga; Alexander Askinadze; Matthias Liebeck; Stefan Conrad; Tobias Hildebrandt; Conrad Indiono; Stefanie Rinderle-Ma; Martin Grimmer; Matthias Kricke; Eric Peukert
The First Data Science Challenge at BTW 2017
Datenbank-Spektrum
2017-09
PDF

Google Scholar
publication iconKricke, Matthias; Grimmer, Martin; Schmeißer, Michael
Preserving Recomputability of Results from Big Data Transformation Workflows
Workshop Proceedings BTW, Lecture Notes in Informatics(LNI), GI 2017
2017-03-07

Supervision of Theses

  • MA Paul Röwer: Skalierbares Clustering geotemporaler Daten auf verteilten Systemen (scalable clustering of geotemporal data on distributed systems)
  • MA Oliver Swoboda: Serverseitige Aggregation von Zeitreihendaten in verteilten NoSQL-Datenbanken (server site aggregation of time-series data in distributed NoSQL databases)