Skip to main content

User account menu

  • Log in
DBS-Logo

Database Group Leipzig

within the department of computer science

ScaDS-Logo Logo of the University of Leipzig

Main navigation

  • Home
  • Study
    • Exams
      • Hinweise zu Klausuren
    • Courses
      • Current
    • Modules
    • LOTS-Training
    • Abschlussarbeiten
    • Masterstudiengang Data Science
    • Oberseminare
    • Problemseminare
    • Top-Studierende
  • Research
    • Projects
      • Benchmark datasets for entity resolution
      • FAMER
      • HyGraph
      • Privacy-Preserving Record Linkage
      • GRADOOP
    • Publications
    • Prototypes
    • Annual reports
    • Cooperations
    • Graduations
    • Colloquia
    • Conferences
  • Team
    • Erhard Rahm
    • Member
    • Former employees
    • Associated members
    • Gallery

Dr. Eric Peukert

Breadcrumb

  • Home
  • Team
  • Dr. Eric Peukert
portrait photo
  • Eric Peukert
  • peukert@informatik.uni-leipzig.de
  • +49 341 97 39 301
  • Data Science Zentrum  - Center for Scalable Data Analytics and Aritficial Intelligence (ScaDS.AI Dresden Leipzig), 
    Humboldstraße 25, 3. OG
    4105 Leipzig

About

  • Since 12/2014 Data Science Zentrum (Zentrum für skalierbare Datenanalyse und Künstliche Intelligenz ScaDS.AI Dresden/Leipzig), Management@Universität Leipzig (www.scads.de)

  • 2011 – 2014 Researcher at SAP SE

  • 2007 – 2011 Research Associate at SAP Research CEC Dresden, SAP AG

  • Graduation: Dr. rer. nat., Universität Leipzig, November 2013

  • Diploma in Computer Science and Media, Technische Universität Dresden, July 2007

Research Interests

  • (Temporal) Graph-based Data Integration & Matching
    • FAst Multi-source Entity Resolution system (FAMER)
  • Big Data Frameworks
  • Distributed Image Processing & Matching

Supervision of Thesis/ Lab-Projects

  • Finished

    • Bachelor Thesis: Tim Matzek, Distributed Sum-Formula Lookup-Service (joint supervision with Dr. Oliver Lechtenfeld and Kai Franze from UFZ)
    • Master Thesis: Kai Franze, Chemical Rules in Massspectrometry analysis workflows (joint supervision with Dr. Oliver Lechtenfeld from UFZ)
    • Master Thesis: Georges Alkhouri, Deep Learning for Deduplication
    • Master Thesis, Marcel Jacob, Effiziente Haltung und Abfrage geotemporaler Daten im Apache Hadoop-Ökosystem (Joint supervision with Martin Grimmer from MGM technology partners)
    • Kevin Förster, Eignung von Workflow-Management-Tools für BigData- Aufgabenstellungen (co-supervised with Lars-Peter Meyer)
    • Master Thesis , Wolfgang Amman, Vergleich und Evaluation von RDF-on-Hadoop Lösungen
    • Master Thesis, Kevin Jacob, Verwaltung und Verarbeitung von Massenspektrometerdaten (joint supervision with Dr. Anika Groß from DBS-Group and Dr. Oliver Lechtenfeld, Julia Raeke from UFZ)
    • Master Thesis, Florian Pretsch, Entwicklung von Techniken zur Datenintegration und Datenqualitätsverbesserung für die Graph-Processing-Platform GRADOOP (Joint supervision with Prof. Thor from HFTL)
    • Bachelor Thesis: Katharina Thießen, Dedoop in KNIME
    • Bachelor Thesis: Christian Fuß, Graph-based Similarity Measure for Matching in Gradoop
    • Master Thesis: Christopher Rost, Image-based Deduplication
    • Bachelor Thesis: Marc Stöhr, Graph-Transformation in Gradoop
  • Lab-Projects

    • SHK, Florens Rohde, Machine Learning for FAMER
    • SHK, Volodymyr Moroz, Graph Analytics Workflows in the Gradoop Service
    • SHK, Anja Neumann, Visual Analytics of metabolic networks with the Gradoop Service
    • SHK, Simon Hüning, Command Line Interface for Dedoop (finished)
    • SHK, Falco Kirchner, Imputation with SLURM on HPC and Shared Nothing Architectures (Joint supervision with Holger Kirsten from IMISE)(finished)
  • Open Topics and Working Student Positions (see www.scads.de)

Teaching

  • Supporting Big Data Praktikum 2016, 2017, 2018
  • Organizing Big Data Ringvorlesung 2017
  • Vorlesung Cloud Data Management CDM 2017/18
  • Vorlesung Cloud Data Management CDM 2019
  • Vorlesung Cloud und Big Data Management CBDM 2020/21
  • Vorlesung Cloud und Big Data Management CBDM 2021/22
  • Vorlesung Cloud und Big Data Management CBDM 2022/23

Publications (25)

Dateien Cover Beschreibung Jahr
The Future is Big Graphs! A Community View on Graph Processing Systems
Sakr, E. ; Bonifati, A. ; Voigt, H. ; Iosup, A. ; Peukert, E.
In CACM to be published
2020 / 12
KOBRA: Praxisfähige lernbasierte Verfahren zur automatischen Konfiguration von Business-Regeln in Duplikaterkennungssystemen
Braun, S. ; Alkhouri, G. ; Peukert, E.
GI-Jahrestagung, LNI
2020 / 9
Incremental Multi-source Entity Resolution for Knowledge Graph Completion
Saeedi, A. ; Peukert, E. ; Rahm, E.
Proc. ESWC
2020 / 6
Graph data transformations in GRADOOP
Kricke, M. ; Peukert, E. ; Rahm, E.
Proc. BTW, March 2019
2019 / 3
Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities
Rahm, E. ; Nagel, W. ; Peukert, E. ; Jäkel, R. ; Gärtner, F. ; Stadler, P. ; Wiegreffe, D. ; Zeckzer, D. ; Lehner, W.
Datenbank-Spektrum 19 (1)
2019 / 3
BIGGR: Bringing Gradoop to Applications
Rostami, M. ; Kricke, M. ; Peukert, E. ; Kühne, S. ; Wilke, M. ; Dienst, S. ; Rahm, E.
Datenbank-Spektrum
2019 / 3
Scalable Matching and Clustering of Entities with FAMER
Saeedi, A. ; Nentwig, M. ; Peukert, E. ; Rahm, E.
Complex Systems Informatics and Modeling Quarterly (CSIMQ), Issue 16, Sep./Oct. 2018, pp 61–83
2018 / 11
ScaDS Dresden/Leipzig – A competence center for collaborative big data research
Jäkel, R. ; Peukert, E. ; Nagel, W. ; Rahm, E.
it-Information Technology
2018 / 11
Using Link Features for Entity Clustering in Knowledge Graphs
Saeedi, A. ; Peukert, E. ; Rahm, E.
Proc. ESWC 2018 (Best research paper award)
2018 / 6
Interactive Visualization of Large Similarity Graphs and Entity Resolution Clusters
Rostami, M. ; Saeedi, A. ; Peukert, E. ; Rahm, E.
Proc. EDBT 2018
2018 / 3

Pagination

  • Current page 1
  • Page 2
  • Page 3
  • Next page Next ›
  • Last page Last »

Recent publications

  • 2025 / 8: Slice it up: Unmasking User Identities in Smartwatch Health Data
  • 2025 / 6: SecUREmatch: Integrating Clerical Review in Privacy-Preserving Record Linkage
  • 2025 / 5: Federated Learning With Individualized Privacy Through Client Sampling
  • 2025 / 3: Assessing the Impact of Image Dataset Features on Privacy-Preserving Machine Learning
  • 2025 / 3: Automated Configuration of Schema Matching Tools: A Reinforcement Learning Approach

Footer menu

  • Directions
  • Contact
  • Impressum