Prof. Dr. Stephan Günnemann

Technical University of Munich
Department of Informatics - I3
Boltzmannstr. 3
85748 Garching b. München
Germany

Room: 02.11.055
Phone: +49 (0)89 / 289-17282
Fax: +49 (0)89 / 289-17257
E-Mail: guennemann@in.tum.de

Research Focus

  • Graph Mining, Network Analysis, Robust and Scalable Learning for Attributed Graphs
  • Subspace Clustering, Multi-View Clustering, Mining and Learning of High Dimensional Data
  • Probabilistic Graphical Models, Bayesian Statistics
  • Analysis of Temporal and Dynamic Data

Research Background

  • Professor
    Technische Universität München, Munich, Germany
    since October 2016
  • Research Group Leader
    Technische Universität München, Munich, Germany
    July 2015 - September 2016
    • funded by the Emmy Noether Program of the German Research Foundation (DFG)
  • Research Scientist
    Siemens AG, Siemens Research & Technology Center, Munich, Germany
    February 2015 - June 2015
  • Senior Researcher
    Carnegie Mellon University, Pittsburgh, USA
    October 2014 - February 2015
  • Post-Doctoral Researcher
    Carnegie Mellon University, Pittsburgh, USA
    October 2012 - September 2014
  • Visiting Researcher
    Simon Fraser University, Vancouver, Canada
    May 2011 - June 2011
  • Research Associate
    Data Management and Data Exploration Group, RWTH Aachen University
    July 2008 - September 2012
  • Promotion [Ph.D.] at the RWTH Aachen University (June 2008 - March 2012)
    • Dissertation (Ph.D. thesis) "Subspace Clustering for Complex Data"
    • Graduated with distinction "summa cum laude"
  • Studies in Computer Science at RWTH Aachen Universiy (October 2003 - May 2008)
    • Diplomarbeit (Master thesis) "Approximations for efficient subspace clustering in high-dimensional databases"
    • Graduated with distinction

Academic Honors and Awards

  • Microsoft Azure Research Award, 2017
  • Rudolf Mößbauer Fellowship of the TUM Institute for Advanced Study, 2016
  • Emmy Noether Research Grant of the German Research Foundation (DFG) to set up an independent research group, 2015
  • Young Researcher at the Heidelberg Laureate Forum, Heidelberg, Germany, 2015
  • Best Student Paper Runner-Up Award for the paper ``Com2: Fast Automatic Discovery of Temporal ('Comet') Communities`` at the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2014
  • Dissertation Award of the German Computer Science Society, Section on Databases and Information Systems, 2013
  • DAAD Scholarship for postdoctoral research at the Carnegie Mellon University for the period 10/2013 to 09/2014
  • Borchers-Plakette for doctoral dissertation "Subspace Clustering for Complex Data", 2013
  • Travel Award for the paper ``Finding Contexts of Social Influence in Online Social Networks`` at the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Workshop on Social Network Mining and Analysis, 2013
  • DAAD Scholarship for postdoctoral research at the Carnegie Mellon University for the period 10/2012 to 09/2013
  • Best Paper Award for the paper "DB-CSC: A density-based approach for subspace clustering in graphs with feature vectors" at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2011
  • Friedrich-Wilhelm-Preis for diploma thesis on "Approximations for efficient subspace clustering in high-dimensional databases", 2009
  • Springorum-Denkmünze for Diplom (Master of Science) in Computer Science with overall mark 'excellent', 2009
  • Schöneborn-Preis for the year's best Vordiplom (Bachelor degree equivalent) in Computer Science at the RWTH Aachen University, 2006

Scientific Community Services

Editor

  • Associate Editor of the Knowledge and Information Systems Journal, since 2015
  • Guest Editor of the Machine Learning Journal. Special issue ``MultiClust: Discovering, Summarizing and Using Multiple Clusterings'', 2012-2015

Organization

  • Organization committee co-chair of the 2017 International Conference on Very Large Data Bases (VLDB)
  • Program co-chair of the 2016 LWDA conference (joint conference of the special interest groups IR, KDML, WM, and DB of the German Computer Science Society)
  • Member of the organizing committee for the 2016 Emmy Noether meeting
  • Organizer of the tutorial "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the International Conference on Machine Learning (ICML 2013), Atlanta, Georgia, USA
  • Organizer of the tutorial "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2012), Kuala Lumpur, Malaysia
  • Organizer of the tutorial "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the IEEE International Conference on Data Engineering (ICDE 2012), Washington, DC, USA
  • Co-Chair "2nd MultiClust Workshop on Discovering, Summarizing and Using Multiple Clusterings" (MultiClust 2011) held in conjunction with ECML PKDD 2011, Athens, Greece
  • Organizer of the tutorial "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the SIAM International Conference on Data Mining (SDM 2011), Mesa, Arizona, USA
  • Organizer of the tutorial "Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data", at the IEEE International Conference on Data Mining (ICDM 2010), Sydney, Australia
  • Slides of our tutorial are available here.

Program committee member

  • KDD 2014, 2015, 2016, 2017 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining)
  • ICDM 2017 Area Chair (IEEE International Conference on Data Mining)
  • WWW 2015, 2016, 2017 (International World Wide Web Conference)
  • ECML PKDD 2012, 2016, 2017 (European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases)
  • CIKM 2012, 2013, 2014, 2015, 2016 (ACM International Conference on Information and Knowledge Management)
  • SDM 2015, 2016, 2017 (SIAM International Conference on Data Mining )
  • PAKDD 2016, 2017 (Pacific-Asia Conference on Knowledge Discovery and Data Mining)
  • IDEA 2017 (Workshop on Interactive Data Exploration and Analytics)
  • HPGDMP 2016 (Workshop on High Performance Graph Data Management and Processing)
  • HPGP 2016 (Workshop on High Performance Graph Processing)
  • KDML 2013, 2014, 2015, 2016 (Workshop on Knowledge Discovery, Data Mining and Machine Learning)
  • HDM 2013, 2014, 2015, 2016 (Workshop on High Dimensional Data Mining)
  • MANEM 2015 (Workshop on Multiplex and Attributed Network Mining)
  • MASS 2015 (Workshop on Mobility Analytics from Spatial and Social Data)
  • BGM 2014 (Workshop on Big Graph Mining)
  • SIGMOD 2013 (ACM SIGMOD International Conference on Management of Data)
  • MultiClust 2011, 2012, 2013 (Workshop on Discovering, Summarizing and Using Multiple Clusterings)

Reviewer for International Journals

  • The VLDB Journal (VLDBJ)
  • Data Mining and Knowledge Discovery Journal (DAMI)
  • Data & Knowledge Engineering Journal (DKE)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS/TNN)
  • Maching Learning Journal (MLj)
  • Information Sciences

Invited Talks

  • ``Beyond Independence: Efficient Learning Techniques for Networks and Temporal Data'', at the Berlin Big Data Center, TU Berlin, Berlin, Germany, November 2016
  • ``Mining Large-Scale Network Data'', at the Big Data meeting of the German Academic Exchange Service, Garching, Germany, November 2016
  • ``Robust Data Analytics for Large-Scale Attributed Graphs'', at the annual meeting of the GI-Beirat der Universitätsprofessoren, Schloss Dagstuhl, Wadern, Germany, March 2016
  • ``Robust Mining of Temporal and Network Data'', at the Max Planck Institute for Informatics, Saarbrücken, Germany, January 2015
  • ``Beyond Independence: Unsupervised Learning for Temporal and Network Data'', at Amazon.com, Inc., Berlin, Germany, September 2014
  • ``Tackling the Challenge of Variety: Data Mining Methods for Complex Data'', at the Technische Universität München, Germany, March 2014
  • ``Advanced Subspace Clustering Techniques'', at the IEEE International Conference on Data Mining, Workshop on High Dimensional Data Mining, Dallas, Texas, USA, December 2013
  • ``Subspace Clustering for Complex Data'', at the GI Conference on Database Systems for Business, Technology, and the Web, Magdeburg, Germany, March 2013
  • ``Mining Coherent Subgraphs in Multi-Layer Graphs with Edge Labels'', at the Carnegie Mellon University, Pittsburgh, Pennsylvania, USA, October 2012
  • ``Subspace Clustering: Recent Challenges and Future Directions'', at the Simon Fraser University, Vancouver, Canada, June 2011
  • ``Subspace Clustering: Introduction and Advanced Models'', at the University of Antwerp, Belgium, April 2011

Teaching Activities

Please visit this site for my teaching activities at TUM. An overview of my past teaching experience is summarized here.

Software

KDD-SC: Subspace Clustering Extensions for Knowledge Discovery Frameworks

http://dme.rwth-aachen.de/KDD-SC/

Technical Report

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