In Press  
The Blind Men and the Elephant: About Meeting the Problem of Multiple Truths in Data from Clustering and Pattern Mining Perspectives. Machine Learning, Springer (IF 1.587) (In Press) 

2014  
Narrow or Broad? Estimating Subjective Specificity in Exploratory Search. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM'14), ACM, 2014. (IR track full paper, overall 21% acceptance rate) 

A Fresh Look on Knowledge Bases: Distilling Named Events from News. In: Proceedings of ACM Conference on Information and Knowledge Management (CIKM'14), ACM, 2014. (KM track full paper, overall 21% acceptance rate) 

Multivariate Maximal Correlation Analysis. In: Proceedings of the International Conference on Machine Learning (ICML'14), JMLR: W&CP vol.32, 2014. (25.0% acceptance rate) 

VoG: Summarizing and Understanding Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM'14), SIAM, 2014. (fast track journal invitation, as one of the best of SDM'14; full paper with presentation, 15.4% acceptance rate) 

Interesting Patterns. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 105134, pp 105134, Springer, 2014. 

Frequent Pattern Mining and Compression  Mining Useful Patterns by MDL. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 165198, pp 165198, Springer, 2014. 

Frequent Pattern Mining Algorithms for Data Clustering. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 403424, pp 403424, Springer, 2014. 

mdl4bmf: Minimal Description Length for Boolean Matrix Factorization. Transactions on Knowledge Discovery from Data, pp 130, ACM (IF 1.68) 

Uncovering the Plot: Detecting Surprising Coalitions of Entities in MultiRelational Schemas. Data Mining and Knowledge Discovery vol.28(5), pp 13981428, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track) 

Unsupervised InteractionPreserving Discretization of Multivariate Data. Data Mining and Knowledge Discovery vol.28(5), pp 13661397, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track) 

Efficiently Spotting the Starting Points of an Epidemic in a Large Graph. Knowledge and Information Systems vol.38(1), pp 3559, Springer, 2014. (IF 2.225) 

Efficient Discovery of the Most Interesting Associations. Transactions on Knowledge Discovery from Data vol.8(3), pp 131, ACM, 2014. (IF 1.68) 

2013  
Cartification: A Neighborhood Preserving Transformation for Mining High Dimensional Data. In: Proceedings of the IEEE International Conference on Data Mining (ICDM'13), pp 937942, IEEE, 2013. (19.6% acceptance rate) 

Detecting Bicliques in GF[q]. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD'13), pp 509524, Springer, 2013. 

Maximum Entropy Models for Iteratively Identifying Subjectively Interesting Structure in RealValued Data. In: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD'13), pp 256271, Springer, 2013. 

CMI: An InformationTheoretic Contrast Measure for Enhancing Subspace Cluster and Outlier Detection. In: Proceedings of the SIAM International Conference on Data Mining (SDM'13), pp 198206, SIAM, 2013. (oral presentation, 14.4% acceptance rate; overal 25%) 

Mining Connection Pathways for Marked Nodes in Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM'13), pp 3745, SIAM, 2013. (oral presentation, 14.4% acceptance rate; overal 25%) 

Summarizing Categorical Data by Clustering Attributes. Data Mining and Knowledge Discovery vol.26(1), pp 130173, Springer, 2013. (IF 2.877) 
Exploratory Data Analysis group
Cluster of Excellence MMCI
Saarland University
66123 Saarbrücken, Germany
Since October 2013, I lead the independent research group on Exploratory Data Analysis at the DFG clusterofexcellence on Multimodal Computing and Interaction at the University of Saarland.
In addition, I'm affiliated as
Senior Researcher with the Database and Information Systems (D5) group of the Max Planck Institute for Informatics.
My research is mainly concerned with exploratory data mining. That is, I develop theory and algorithms for answering the question `this is my data, tell me what I need to know'. To identify what you need to know, i.e., what is the most interesting structure in the data, I often employ wellfounded statistical methods. In particular, Information Theory — the principles of Minimum Description Length (MDL) and Maximum Entropy have proven to be highly valuable tools. Next, I develop highly efficient algorithms for extracting these interesting structures, i.e., models, from very large and complex data—as well as investigate how we can use these structures in a wide range of applications, including identifying rare diseases, ehealth, bioinformatics, market analysis, product recommendation, etc.
I'm always looking for talented and motivated
PhD candidates, postdocs, and HiWi's
with a strong background in data mining, machine learning, statistics, and/or mathematics.
Currently I'm investigating techniques for identifying informative local structures in large collections of complex data; how to efficiently mine good data descriptions directly such data; the theoretical and practical foundations of interactive exploration of very large data, discovering things by serendipity; how to mine large relational databases; how to mine very large graphs, including characterising influence propagation in social networks; as well as to study wellfounded approaches for meaningfully comparing between, and validation of, explorative results.
Below, you'll find an overview of my activities, as well as a selection of my recent publications. You might further be interested in my publications, implementations, our tutorial on Information Theoretic Methods in Data Mining at ECML PKDD'14, or our workshop on Interactive Data Exploration and Analytics (IDEA) at KDD'14.
or, in case you're looking for a bit of procrastination, consider
Research in Progress — the secret life of research, through the medium of animated GIFs.
 Organisation & Invited Talks
 Program CoChair of ECML PKDD 2016, Riva del Garda, Italy.
 Publicity CoChair of ACM IUI 2015, Atlanta, USA.
 Sponsorship CoChair of ECML PKDD 2014, Nancy, France.
 Workshop CoChair of IEEE ICDM 2012, Brussels, Belgium.
 Organiser of the ACM SIGKDD 2014 Workshop on Interactive Data Exploration and Analytics (IDEA), NYC, USA.
 Organiser of the ACM SIGKDD 2013 Workshop on Interactive Data Exploration and Analytics (IDEA), Chicago, USA.
 Organiser of the ACM SIGKDD 2013 Workshop on Outlier Detection and Description (ODD), Chicago, USA.
 Organiser of the ECML PKDD 2012 Workshop on Instant Interactive Data Mining (IID), Bristol, UK.
 Organiser of the ACM SIGKDD 2010 Workshop on Useful Patterns (UP), Washington DC, USA.
 Organiser of the ECML PKDD 2014 Tutorial on Information Theoretic Methods in Data Mining, Nancy.
 Organiser of the IEEE ICDM 2011 Tutorial on Mining Sets of Patterns, Vancouver, Canada.
 Organiser and speaker of the ECML PKDD 2010 Tutorial on Mining Sets of Patterns, Barcelona, Spain.
 Invited speaker at the IEEE ICDM 2013 PhD Forum, Dallas, Texas.
 Invited speaker at the IEEE ICDM 2011 Workshop on Data Mining for Computational Collective Intelligence.
 Invited speaker at the ECML PKDD 2008 Workshop From Local Patterns to Global Models, Antwerp, Belgium.

Awards & Grants
 ACM SIGKDD'11 Best Student Paper Award for 'Tell Me What I Need to Know'
 ACM SIGKDD'10 Doctoral Dissertation RunnerUp Award
 ECML PKDD'09 Best Student Paper Award for 'Identifying the Components'
 UdSCS 'Topics in Algorithmic Data Analysis (TADA)' received highest rating over all SS'14 Advanced Lectures.
 Young Researcher at the Heidelberg Laureate Forum 2014, Heidelberg, Germany.
 Independent Research Group 'Exploratory Data Analysis' at the Cluster of Excellence MMCI at U.Saarland ('13–'18)
 Research Project 'Instant, Interactive & Adaptive Data Mining' of the Research Foundation – Flanders (FWO) ('12–'15)
 PostDoctoral Fellowship of the Research Foundation – Flanders (FWO) ('10–'13)
 UABOFKP Small Project (2010)
 UABOFIWS Postdoctoral Researcher ('09–'10)

Journal Reviewing
 Member of the Guest Editorial Board for the ECML PKDD Journal Track '13–'15
 Data Mining and Knowledge Discovery (DAMI)
 Transactions on Knowledge Discovery and Data Mining (TKDD)
 Transactions on Knowledge and Data Engineering (TKDE)
 Maching Learning journal (MLj)
 Information Systems (IS)
 Knowledge and Information Systems (KAIS)
 Social Network Analysis and Mining (SNAM)
 Statistical Analysis and Data Mining (SAM)
 Transactions on Intelligent Systems and Technology (TIST)

Program Committees
 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) '10–'14
 ACM International Conference on Knowledge and Information Management (CIKM) '12–'13
 IEEE International Conference on Data Mining (ICDM) '12, '14
 IEEE International Conference on Data Engineering (ICDE) '13
 SIAM Conference on Data Mining (SDM) '10,'11,'15
 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery
in Databases (ECML PKDD) '08–'14, area chair '14  European Conference on Artificial Intelligence (ECAI) '14
 Intelligent User Interfaces (IUI) senior PC '15
 International Conference on Advances in Social Network Analysis and Mining (ASONAM) '12
 International Conference on Pattern Recognition Applications and Methods (ICPRAM) '12
 BelgianDutch Conference on Machine Learning (BENELEARN) '13
 Workshop on Big Graph Mining (BGM) '14)
 Workshop on Optimization Methods for Anomaly Detection (OMAD) '14
 Workshop on Practical Theories for Exploratory Data Mining (PTDM) '12
 Workshop on Discovering, Summarizing and Using Multiple Clusterings (MultiClust) '11–'13
 Workshop From Local Patterns to Global Models (LeGo) '08–'09

Graduate Courses
 The Information Theory Seminar (WS'14)
 Topics in Algorithmic Data Analysis (SS'14)
 Advanced Data Mining ('09–'13)
 Project Databases ('09–'10)
 Database Security ('09–'10)

Undergraduate Courses
 Artificial Intelligence ('12–'13)
 Introduction to Artificial Intelligence ('09–'12)
 Introduction to Data Mining ('09–'11)
 Internet Programming ('06–'08)
 Databases ('05–'06)

Graduate Students
 Sinan Bozca
 Kailash Budhathoki
 Eustace Ebhotemhen
 Shilpa Garg
 Manan Ghandi
 Panagiotis Mandros
 Stefan Neumann
 Dr. Koen Smets (16 May 2012)
 Dr. Michael Mampaey (21 Oct 2011)
 Thomas Van Brussel, MSc (2012)
 Tanja Van den Eede, MSc (2011)
 Sandy Moens, MSc (2010)
 Andie Similon, MSc (2010)
 Sander Schuckmann, MSc (2009)