Dr. rer. nat. Emmanuel Müller

Research associate
Email:mueller@informatik.rwth-aachen.de
Website:http://www.ipd.kit.edu/~muellere/
Publications: 51 entries

Since November 2010, Dr. Müller is not at RWTH Aachen University. Further information can be found on the website of Dr. rer. nat. Emmanuel Müller at the Karlsruhe Institute of Technology (KIT).

 

 

Research focus:

  • Efficient knowledge discovery in large databases
    • Subspace clustering
    • Outlier mining
    • Data mining in high dimensional databases
  • Applications in
    • Bioinformatics
    • Mobile communication networks
    • Business intelligence


Main research project:

UMIC-Logo

Research cluster UMIC

Research area B:

Mobile Stream Data Mining

Research area D:

Energy awareness of mobile applications

Further research projects and collaborations:

  • [2006-2010] Research project Subspace Mining
  • [2007-2008] European union project NISIS
  • [2007] Chair of Pathology (Dr. Michael Baudis)
  • [2007-2009] Chair of Cell Biology (Prof. Martin Zenke)
  • [2008] National Instruments (Stefan Romainczyk)
  • [2008] AT&T Labs Research (Divesh Srivastava, PhD)
  • [2008] Virtual Reality Center Aachen (Dr. Torsten Kuhlen)
  • [2008] Institute of Molecular Biotechnology (Dr. Kurt Hoffmann)
  • [2008-2010] Research project Outlier Ranking
  • [2009] SAP Research Center in Karlsruhe (Nina Oertel)
  • [2009] Aucos Elektronische Geräte GmbH (Egbert König)

Open Source Project for Subspace Clustering:

OpenSubspace:
An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA

http://dme.rwth-aachen.de/OpenSubspace/

 

Evaluation Study (VLDB 2009):

Evaluating Clustering in Subspace Projections of High Dimensional Data

http://dme.rwth-aachen.de/OpenSubspace/evaluation

 

Tutorials at international conferences:

  • [ICDM 2010] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the IEEE International Conference on Data Mining, Sydney, Australia (2010)
  • [SDM 2011] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the SIAM International Conference on Data Mining, Mesa, Arizona, USA (2011)
  • [ICDE 2012] "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the IEEE International Conference on Data Engineering, Washington, DC, USA (2012)

    Slides and additional information will be available on our tutorial website.

 

Workshop Organization:

  • [MultiClust 2011] "2nd MultiClust Workshop on Discovering, Summarizing and Using Multiple Clusterings" held in conjunction with ECML PKDD 2011, Athens, Greece 5-9 Sep. 2011

 

Teaching:

  • Lecturer in the course
    • Advanced Data Mining Algorithms, SS 2010
  • Exercises in the courses:
    • Data Mining Algorithms, WS 2008/09
    • Advanced Data Mining Algorithms, SS 2008
    • Index Structures, WS 2007/08
  • Supervision of practical courses:
    • Softwarepraktikum "Anwendung und Evaluierung von Data Mining Techniken", SS 2009
    • Data Mining Algorithms, WS 2008/09
    • Data Mining Algorithms, WS 2007/08
    • Softwarepraktikum "Datenstrukturen", SS 2007
  • Regularly supervision of seminar theses

 

INTEGER teaching concept:

INTEGER (INTEGration of Education and Research) is a concept for the integration of teaching and research. A project description, achieved results and publications are listed on the INTEGER webpage. In INTEGER the following students have been supervised in an early stage of their scientific career, as part of practical lab courses or as student assistants.

  • Sebastian Raubach
  • Patrick Gerwert
  • Matthias Hannen
  • Thomas Mausbach
  • Pascal Spaus
  • Yannick Thill
  • Leonid Pishchulin (research assistant)
  • Marian Van de Veire
  • Ines Färber (research assistant)
  • Sergej Fries (research assistant)
  • Anca-Maria Ivanescu (research assistant)
  • Timm Jansen
  • Matthias Schiffer (research assistant)
  • Michael Nett (aiming at a research career)
  • Felix Reidl (aiming at a research career)

 

Supervised Theses (bachelor, master and diploma theses):

  • Sebastian Raubach (with Stephan Günnemann)
  • Thomas Ramm
  • Charlotte Laufkötter (with Stephan Günnemann and Hardy Kremer)
  • Adriola Faqolli (with Marwan Hassani)
  • Lingyu Wang
  • Ines Färber (with Stephan Günnemann)
  • Matthias Schiffer
  • Stephan Günnemann (with Ira Assent and Ralph Krieger)
  • Babak Ahmadi (with Ira Assent and Ralph Krieger)
  • Thorsten Wessling (with Philipp Kranen)
  • Uwe Steinhausen (with Ira Assent and Ralph Krieger)

Reviews:

  • International Conferences and Journals:
    • VLDB Journal (International Journal on Very Large Data Bases)
    • KDD 2010 (Knowledge Discovery and Data Mining)
    • SSDBM 2010 (International Conference on Scientific and Statistical Database Management)
    • SDM 2010 (SIAM International Conference on Data Mining)
    • EDBT 2010 (International Conference on Extending Database Technology)
    • ICDE 2010 (IEEE International Conference on Data Engineering)
    • DMKD Journal (Data Mining and Knowledge Discovery Journal)
    • KDD 2009 (Knowledge Discovery and Data Mining)
    • DKE Journal (Data & Knowledge Engineering Journal)
    • EDBT 2009 (International Conference on Extending Database Technology)
    • ICDE 2009 (IEEE International Conference on Data Engineering)
    • EDBT 2008 (International Conference on Extending Database Technology)
    • ICDE 2008 (IEEE International Conference on Data Engineering)

 

Research Background:

  • Research assistant at Chair of Computer Science 9 (Feb. 2007 - Oct. 2010)
  • Promotion [Ph.D.] (Feb. 2007 - Jun. 2010):
    • Graduated as Dr. rer. nat. at RWTH Aachen
    • Dissertation (Ph.D. thesis) "Efficient Knowledge Discovery in Subspaces of High Dimensional Databases"
    • Graduated with distinction "summa cum laude"
  • Studies (WS 2002/03 - WS 2006/07):
    • Graduated in Computer science at RWTH Aachen
    • Diplomarbeit (master thesis) "Efficient density-based subspace clustering"
    • Graduated with distinction

 

Languages:

  • German
  • English
  • Greek

 

 

Thesis

Efficient Knowledge Discovery in Subspaces of High Dimensional Databases

Tutor: Seidl T.
Type: Dissertation