Jilles Vreeken

Independent Research Group Leader (W2)
Exploratory Data Analysis group
Cluster of Excellence MMCI
Saarland University

Senior Researcher
Databases and Information Systems
Max Planck Institute for Informatics

Campus E 1.7 Room 3.22

66123 Saarbrücken, Germany

jilles@mpi-inf.mpg.de

+49 681 302 71 925

+49 681 302 70 155

Jilles at work in South Africa

Since October 2013, I lead the independent research group on Exploratory Data Analysis at the DFG cluster-of-excellence 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 well-founded 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, e-health, bio-informatics, 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 well-founded 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 tutorials on Information Theoretic Methods in Data Mining at ECML PKDD'14 and SIAM SDM'15, 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.

Activities more ▾

Organisation & Invited Talks
- Program Co-Chair of ECML PKDD 2016, Riva del Garda, Italy.
- Publicity Co-Chair of ACM IUI 2015, Atlanta, USA.
- Sponsorship Co-Chair of ECML PKDD 2014, Nancy, France.
- Workshop Co-Chair of IEEE ICDM 2012, Brussels, Belgium.
- Organizer of the International Workshop Data Mining: Beyond the Horizon, November 2014, Bristol, UK.
- 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 SIAM SDM 2015 Tutorial on Information Theoretic Methods in Data Mining, Vancouver, Canada.
- Organiser of the ECML PKDD 2014 Tutorial on Information Theoretic Methods in Data Mining, Nancy, France.
- 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 Runner-Up Award
- ECML PKDD'09 Best Student Paper Award for 'Identifying the Components'
- UdS-CS '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)
- Post-Doctoral Fellowship of the Research Foundation – Flanders (FWO) ('10–'13)
- UA-BOF-KP Small Project (2010)
- UA-BOF-IWS Postdoctoral Researcher ('09–'10)
Editorial Board Memberships
- Data Mining and Knowledge Discovery (DAMI) since '15
- Guest Editorial Board for the ECML PKDD Journal Track '13–'15
Journal Reviewing
- Transactions on Knowledge Discovery and Data Mining (TKDD)
- Transactions on Knowledge and Data Engineering (TKDE)
- Maching Learning journal (MLj)
- Statistical Analysis and Data Mining (SAM)
- Information Systems (IS)
- Knowledge and Information Systems (KAIS)
- Social Network Analysis and Mining (SNAM)
- Transactions on Intelligent Systems and Technology (TIST)
Program Committees
- ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD) '10–'15
- ACM International Conference on Knowledge and Information Management (CIKM) '12–'13
- IEEE International Conference on Data Mining (ICDM) '12,'14,'15
- 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

Teaching more ▾

Graduate Courses
- The Information Theory Seminar (WS'14)
- Topics in Algorithmic Data Analysis (SS'14)
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)

Research Assistants
- Apratim Bhattacharyya
- Sebastian Brust
- Kailash Budhathoki
- Eustace Ebhotemhen
- Manan Gandhi
- Panagiotis Mandros
- Stefan Neumann

PhD Thesis Supervision
- Dr. Koen Smets (16 May 2012)
- Dr. Michael Mampaey (21 Oct 2011)

MSc Thesis Supervision
- Thomas Van Brussel, MSc (2012)
- Tanja Van den Eede, MSc (2011)
- Sandy Moens, MSc (2010)
- Andie Similon, MSc (2010)
- Sander Schuckmann, MSc (2009)

Selected Recent Publications (go here for the complete list)

In Press
	Zimek, A & Vreeken, J 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)
2015
	Vreeken, J Causal Inference by Direction of Information. In: Proceedings of the SIAM International Conference on Data Mining (SDM'15), SIAM, 2015.
	Karaev, S, Miettinen, P & Vreeken, J Getting to Know the Unknown Unknowns: Destructive-Noise Resistant Boolean Matrix Factorization. In: Proceedings of the SIAM International Conference on Data Mining (SDM'15), SIAM, 2015.
	Sundareisan, S, Vreeken, J & Prakash, BA Hidden Hazards: Finding Missing Nodes in Large Graph Epidemics. In: Proceedings of the SIAM International Conference on Data Mining (SDM'15), SIAM, 2015.
2014
	Atukorala, K, Oulasvirta, A, Glowacka, D, Vreeken, J & Jaccuci, G 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)
	Kuzey, E, Vreeken, J & Weikum, G 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)
	Nguyen, H-V, Müller, E, Vreeken, J & Böhm, K Multivariate Maximal Correlation Analysis. In: Proceedings of the International Conference on Machine Learning (ICML'14), pp 775-783, JMLR: W&CP vol.32, 2014. (25.0% acceptance rate)
	Koutra, D, Kang, U, Vreeken, J & Faloutsos, C VoG: Summarizing and Understanding Large Graphs. In: Proceedings of the SIAM International Conference on Data Mining (SDM'14), pp 91-99, SIAM, 2014. (fast track journal invitation, as one of the best of SDM'14; full paper with presentation, 15.4% acceptance rate)
	Vreeken, J & Tatti, N Interesting Patterns. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 105-134, pp 105-134, Springer, 2014.
	van Leeuwen, M & Vreeken, J Mining and Using Sets of Patterns through Compression. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 165-198, pp 165-198, Springer, 2014.
	Zimek, A, Assent, I & Vreeken, J Frequent Pattern Mining Algorithms for Data Clustering. In: Aggarwal, CC & Han, J (eds) Frequent Pattern Mining, pp 403-424, pp 403-424, Springer, 2014.
	Miettinen, P & Vreeken, J mdl4bmf: Minimal Description Length for Boolean Matrix Factorization. Transactions on Knowledge Discovery from Data vol.8(4), pp 1-30, ACM, 2014. (IF 1.68)
	Wu, H, Vreeken, J, Tatti, N & Ramakrishnan, N Uncovering the Plot: Detecting Surprising Coalitions of Entities in Multi-Relational Schemas. Data Mining and Knowledge Discovery vol.28(5), pp 1398-1428, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track)
	Nguyen, H-V, Müller, E, Vreeken, J & Böhm, K Unsupervised Interaction-Preserving Discretization of Multivariate Data. Data Mining and Knowledge Discovery vol.28(5), pp 1366-1397, Springer, 2014. (IF 2.877) (ECML PKDD'14 Journal Track)
	Prakash, BA, Vreeken, J & Faloutsos, C Efficiently Spotting the Starting Points of an Epidemic in a Large Graph. Knowledge and Information Systems vol.38(1), pp 35-59, Springer, 2014. (IF 2.225)
	Webb, G & Vreeken, J Efficient Discovery of the Most Interesting Associations. Transactions on Knowledge Discovery from Data vol.8(3), pp 1-31, ACM, 2014. (IF 1.68)