Peter van der Putten


research interests | scientific publications | popular publications | teaching | student projects | reviewing | events | The Insurance Company (TIC) benchmark


Welcome to my academic homepage. I am a guest researcher in the Data Mining Group (Algorithms research cluster) at the Leiden Institute of Advanced Computer Science at Leiden University in the Netherlands and also teach in the Mediatechnology Program in the same institute. In addition I spend most of my time in industry as Director of Decisioning Solutions Worldwide at Pegasystems (previously at Chordiant, KiQ, Frictionless Commerce, Sentient Machine Research and an internship at Shell Brasil); see View Peter van der Putten's profile on LinkedIn.

Research Statement

My background is in artificial intelligence and am fascinated by the ability of machines to learn. 'Just' creating or studying an intelligent system is interesting, but personally I am even more intrigued by the question of how intelligence can evolve or emerge by means of interaction. In addition to this fundamental question I am interested in practical data mining and machine learning methodologies and algorithms; not just the technology itself in isolation, but more how the applicability and adoption of these methods could be improved to drive high impact change in business, science or arts:
  • General purpose methods that improve the applicability of data mining
    • end to end knowledge discovery process support or automation, interactive end to end applications
    • data preparation, data fusion, feature selection and construction
    • automation of data mining algorithms and meta learning
    • naive algorithms
    • benchmarking, evaluation and profiling, bias variance decomposition
    • deployment, decision management, decision support and links to management science
  • Data mining and machine learning case applications
    • business: marketing, risk management, law enforcement, telecommunications, management science and economics
    • arts: creative research, media technology, new and old media
    • science: bioinformatics, medicine

Scientific Publications

Maarten H. Lamers Peter van der Putten Putten and Fons J Verbeek. Observations on Tinkering in Scientific Education. In: Cheok A.D., Nijholt A., Romão T. (Eds.) Entertaining the Whole World Human-Computer Interaction Series. London: Springer-Verlag. 137-145, 2014.

Hafeez Osman, Michel R.V. Chaudron and Peter van der Putten (2014) Interactive Scalable Abstraction of Reverse Engineered UML Class Diagrams. In Proceedings of the 21st Asia-Pacific Software Engineering Conference (APSEC 2014), Jeju, Korea, 2014

Hafeez Osman, Michel R.V. Chaudron, Peter van der Putten and Truong Ho-Quang (2014) Condensing Reverse Engineered Class Diagrams through Class Name Based Abstraction.In Proceedings of the 2014 World Congress on Information and Communication Technologies (WICT), Malacca, Malaysia, 2014.

Dejan Radosavljevik and Peter van der Putten. Large Scale Predictive Modeling for Micro-Simulation of 3G Air Interface Load. In: Proceedings 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2014), New York, August 2014, pp 1620-1629.

Hui Li, Peter van der Putten and Maarten Keijzer. Improving Preference Based Modeling By Capturing Correlations Among Features. Benelearn 2014: Proceedings of the 23rd Annual Belgian Dutch Conference on Machine Learning. Brussels, June 6, 2014, p 6.

Hafeez Osman, M.R.V. Chaudron, and Peter van der Putten. Condensing reverse engineered class diagram using text mining. LIACS Technical Report 2014-02, 2014.

Maarten Lamers, Fons Verbeek and Peter van der Putten. Tinkering in Scientific Education. In: Proceedings 10th International Conference on Advances in Computer Entertainment (ACE 2013) no. Lecture Notes in Computer Science: Springer-Verlag. pp 568-571.

Dejan Radosavljevik and Peter van der Putten. Preventing Churn in Telecommunications: The Forgotten Network. In: Proceedings Advances in Intelligent Data Analysis XII - 12th International Symposium, IDA 2013 no. Lecture Notes in Computer Science. pp 357-368.

Palupi Kusuma, Dejan Radosavljevik, Frank Takes and Peter van der Putten. Combining Customer Attribute and Social Network Mining for Prepaid Mobile Churn Prediction. Benelearn 2013: Proceedings of the 23nd Annual Belgian Dutch Conference on Machine Learning. Nijmegen, June 3, 2013, pp 50-58.

Hafeez Osman, Michel R.V. Chaudron and Peter van der Putten. An Analysis of Machine Learning Algorithms for Condensing Reverse Engineered Class Diagrams. In: Proceedings 2013 IEEE International Conference on Software Maintenance (ICSM). 140-149.

Hui Li, Peter van der Putten and Maarten Keijzer. Recommending Products using Preference Based Modeling. Benelearn 2013: Proceedings of the 22nd Annual Belgian Dutch Conference on Machine Learning. Nijmegen, June 3, 2013, pp 59-67.

Dejan Radosavljevik, Peter van der Putten and Kim Kyllesbech Larsen. Mass Scale Modeling and Simulation of the Air-Interface Load in 3G Radio Access Networks. In: Proceedings The Eleventh International Symposium on Intelligent Data Analysis (IDA 2012), Helsinki, 25-27 October 2012, pp 301-312.

Gert-Jan Den Heijer, Peter van der Putten, Erica Benard, Annemarie Meijer and Fons Verbeek. Explorations in Texture Based Classification for Bacterial Infection in Zebrafish. Benelearn 2012, Gent, May 24-25 2012, pp 13-18.

Hafeez Osman, Michel Chaudron and Peter van der Putten. Classifying Presence of Classes in UML Design using Software Metrics. Benelearn 2012, Gent, May 24-25 2012, p 76.

Peter van der Putten, Cor Veenman, Joaquin Vanschoren, Menno Israel and Hendrik Blockeel (eds). Benelearn 2011: Proceedings of the 20th Annual Belgian Dutch Conference on Machine Learning. The Hague, May 20, 2011.

Adrian M. Kentsch, Walter A. Kosters, Peter van der Putten and Frank W. Takes. Exploratory Recommendations Using Wikipedia’s Linking Structure. Benelearn 2011, The Hague, May 20 2011, pp 61-68.

Dejan Radosavljevik, Peter van der Putten and Kim Kyllesbech Larsen. Customer Satisfaction and Network Experience in Mobile Telecommunications Benelearn 2011, The Hague, May 20 2011, pp 91-92.

Dejan Radosavljevik, Peter van der Putten and Kim Kyllesbech Larsen. The Impact of Experimental Setup in Prepaid Churn Prediction for Mobile Telecommunications: What to Predict, for Whom and Does the Customer Experience Matter? Transactions on Machine Learning and Data Mining, Volume 3, Number 2, October 2010, pp 80-99.

Peter van der Putten and Joost N. Kok. Using Data Fusion to Enrich Customer Databases with Survey Data for Database Marketing. In Jorge Casillas and Francisco José Martínez López (Eds.). Marketing Intelligent Systems Using Soft Computing. Springer Series Studies in Fuzziness and Soft Computing, Vol. 258. 1st Edition.September 2010.

Peter van der Putten. Data Fusion for Direct Marketing. Joint Meeting GfKl - CLADAG 2010. Florence, 8 - 10 September 2010.

Dejan Radosavljevik, Peter van der Putten and Kim Kyllesbech Larsen. The Impact of Experimental Setup on Prepaid Churn Modeling: Data, Population and Outcome Definition. Workshop on Data Mining in Marketing (DMM 2010). Berlin, Germany, July 14, 2010.

Menno Israel, Jetske van der Schaar, Egon L. van den Broek, Marten den Uyl and Peter van der Putten. Multi-Level Visual Alphabets. Proceedings International Conference on Image Processing Theory, Tools and Applications (IPTA 2010). Paris France, July 7-10, 2010.

Peter van der Putten. On Data Mining in Context: Cases, Fusion and Evaluation. PhD Thesis, Leiden Institute of Advanced Computer Science (LIACS), Leiden University. January 19, 2010.

Peter van der Putten, Gabor Melli and Brendan Kitts (eds). Proceedings of the Third International Workshop on Data Mining Case Studies (DMCS 2009). Held at the Fifteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 2009), Paris France, June 2009.

Peter van der Putten, Joost N. Kok and Ling Jun Meng.Profiling Novel Classification Algorithms: Artifical Immune Systems. In Proceedings 7th IEEE International Conference on Cybernetic Intelligent Systems 2008 (CIS2008), London, United Kingdom

Peter Paauwe, Peter van der Putten and Michiel van Wezel DTMC: An Actionable e-Customer Lifetime Value Model Based on Markov Chains and Decision Trees. Proceedings of the 9th International Conference on Electronic Commerce: The Wireless World of Electronic Commerce, 2007, University of Minnesota, Minneapolis, MN, USA, August 19-22, 2007. ACM International Conference Proceeding Series 258 ACM 2007

Peter van der Putten, Laura Bertens, Jinshuo Liu, Ferry Hagen, Teun Boekhout and Fons J. Verbeek. Classification of Yeast Cells from Image Features to Evaluate Pathogen Conditions. Multimedia Content Access: Algorithms and Systems (EI121), IS&T/SPIE International Symposium on Electronic Imaging, 28 January - 1 February 2007, San Jose, California, USA.

Menno Israel, Egon L. van den Broek, Peter van der Putten and Marten J. den Uyl. Visual Alphabets: Video Classification by End Users. In: V.A. Petrushin and L. Khan (eds). Multimedia Data Mining and Knowledge Discovery. 1st edition, Springer Verlag, 2007.

Peter van der Putten, Arnold Koudijs and Rob Walker. A Decision Management Approach to Basel II Compliant Credit Risk Management. Workshop Data Mining for Business Applications (DMBA'06), August 20, 2006, Philadelphia, Pennsylvania, USA.

Jinshuo Liu, Peter van der Putten, Ferry Hagen, Xinmeng Chen, Teun Boekhout and Fons J. Verbeek. Detecting Virulent Cells of Cryptococcus Neoformans Yeast: Clustering Experiments. The 18th International Conference on Pattern Recognition ICPR-2006, Hong Kong, August 20-24 2006.

Peter van der Putten and Joost N. Kok. Data mining and knowledge discovery. In: R.J. Baatenburg de Jong (ed), Prognosis in Head and Neck Cancer, Taylor and Francis, 2005.

Peter van der Putten and Ling Jun Meng. Benchmarking the AIRS Artificial Immune System for Classification. The 17th Belgian-Dutch Conference on Artificial Intelligence (BNAIC'05), Brussels, Belgium, October 2005.

Ling Jun Meng, Peter van der Putten and Haiyang Wang A Comprehensive Benchmark of the Artificial Immune Recognition System (AIRS). In proceedings Advanced Data Mining and Applications, First International Conference, ADMA 2005, Wuhan, China, July 22-24, 2005, Xue Li, Shuliang Wang, Zhao Yang Dong (Eds.), 2005, pp. 575-582.

Menno Israel, Egon van den Broek, Peter van der Putten and Marten den Uyl. Real time automatic scene classification. In R. Verbrugge, N. Taatgen, and L.R.B. Schomaker (Eds.), Proceedings of the Sixteenth Belgium-Netherlands Artificial Intelligence Conference (BNAIC) 2004 , p. 401-402. October 21-22, Groningen - The Netherlands.

Peter van der Putten and Maarten van Someren. A Bias-Variance Analysis of a Real World Learning Problem: The CoIL Challenge 2000. Machine Learning, October 2004, vol. 57, iss. 1-2, pp. 177-195, Kluwer Academic Publishers.

Menno Israel, Egon van den Broek, Peter van der Putten and Marten den Uyl. Automating the Construction of Scene Classifiers for Content-Based Video Retrieval. MDM/KDD'04, August 22, 2004, Seattle, WA, USA.

Peter van der Putten, Arnold Koudijs and Rob Walker. Basel II Compliant Credit Risk Management: the OMEGA Case. 2nd EUNITE Workshop on Smart Adaptive Systems in Finance: Intelligent Risk Analysis and Management. Rotterdam, The Netherlands, May 19, 2004.

Joost N. Kok, Egbert J. W. Boers, Walter A. Kosters, and Peter van der Putten. Artificial Intelligence: Definition, Trends, Techniques, In Knowledge for Sustainable Development: an Insight into the Encyclopedia of Life Support Systems. Volume 1, pp 1095-1107, UNESCO Publishing-Eolss Publishers, Oxford, UK, 2002

Peter van der Putten, Martijn Ramaekers, Marten den Uyl and Joost N. Kok. A Process Model for a Data Fusion Factory. Proceedings 12th Belgian-Dutch Artificial Intelligence Conference BNAIC'2002, Leuven, Belgium, October 21-22, 2002.

Peter van der Putten, Joost N. Kok and Amar Gupta. Why the Information Explosion Can Be Bad for Data Mining, and How Data Fusion Provides a Way Out. Second SIAM International Conference on Data Mining, Arlington, April 11-13, 2002.

Peter van der Putten, Joost N. Kok and Amar Gupta. Data Fusion through Statistical Matching. MIT Sloan School of Management Working Paper No. 4342-02, Cambridge, MA, 2002.

K.A. Smith, S. Chuan and P. van der Putten. Determining the validity of clustering for data fusion, International Workshop on Hybrid Intelligent Systems, 11 - 12 December 2001, Adelaide, Australia.

Michiel C. van Wezel, Walter A. Kosters, Peter van der Putten and Joost N. Kok, Nonmetric Multidimensional Scaling with Neural Networks, IDA 2001 (Advances in Intelligent Data Analysis), The Fourth International Conference, Cascais, Portugal, September 13/15, 2001 (Proceedings, pp. 145-155; Springer Lecture Notes in Computer Science 2189; editors: F. Hoffmann, D.J. Hand, N. Adams, D. Fisher and G. Guimaraes).

Peter van der Putten. Data Fusion: A Way to Provide More Data to Mine in?, Proceedings 12th Belgian-Dutch Artificial Intelligence. Conference BNAIC'2000, November 2000, De Efteling, Kaatsheuvel, The Netherlands (Best Paper Nomination).

Peter van der Putten and Maarten van Someren (eds) . CoIL Challenge 2000: The Insurance Company Case.  Published by Sentient Machine Research, Amsterdam. Also a Leiden Institute of Advanced Computer Science Technical Report 2000-09. June 22, 2000.

Peter van der Putten. Data Fusion for Data Mining: a Problem Statement. Coil Seminar 2000, Chios, Greece, June 22-23, 2000.

Peter van der Putten and M. van Someren (eds). The Benelearn 1999 Competition. SWI, University of Amsterdam, November 2, 1999.

Peter van der Putten. A Datamining Scenario for Stimulating Credit Card Usage by Mining Transaction data.; Proceedings of Benelearn'99, 1999.

Peter van der Putten. Promoting Credit Card Usage by Mining Transaction Data. In: P. Berka (ed.). Workshop notes on Discovery Challenge PKDD-99, Laboratory of Intelligent Systems, University of Economics.  Prague, September 1999.

Peter van der Putten. Data Mining in Direct Marketing Databases. In: Walter Baets (ed). Complexity and Management : A Collection of Essays. World Scientific Publishers, Singapore, 1999.

Peter van der Putten. Utilizing the Topology Preserving Property of Self-Organizing Maps for Classification. MSc Thesis, Cognitive Artificial Intelligence, Utrecht University, NL, 1996.

Peter van der Putten. Utilizing the Topology Preserving Property of Self-Organizing Maps: an overview. Unpublished Paper. Dept. of Computer Science, Utrecht University NL, 1994.

Hans van Maaren and Peter van der Putten (eds). Congres Operations Research and Artificial Intelligence. WBBM Delft University and CKI Utrecht University, January 10, 1994.
 

A Selection of Popular Publications (drafts, some in Dutch)

Peter van der Putten. Data Mining is Dood, Lang Leve Decisioning. Database Magazine, nr 3, May 2009

Peter van der Putten and Maarten Keijzer. Chordiant Recommendation Advisor: Adaptive and Rule Based Decisioning for Real Time Marketing. KDD 2006 Demo, Philadelphia 2006.

Peter van der Putten. Broodnodige Intelligentie voor CRM. In Database Magazine, nr 7, November 2002.

Peter van der Putten. Advertising Strategy Discovery. In J. Meij (ed). Dealing with the Data Flood: Mining Data, Text and Multimedia, pp. 247-261, STT 65, STT The Hague, 2002.

Peter van der Putten. Analytical Customer Relationship Management for Insurance Policy Prospects. In (Meij 2002), pp. 293-297.

Peter van der Putten. Matching.  In (Meij 2002), pp. 308-319.

Peter van der Putten and Marten J. den Uyl. Mining E-markets. IT Monitor 3, March 2001.

Peter van der Putten. Datamining in Bedrijf. Informatie en Informatiebeleid 17:3, November 1999.

Peter van der Putten. Vicar Video Navigator: Content Based Video Search Engines Become a Reality. Broadcast Hardware International, IBC edition, September 1999. 
[zipped postscript 762K]

Peter van der Putten. Graven naar Klantgegevens. Informatie en Informatiebeleid 17:2, June 1999.
[zipped postscript 51K]

Peter van der Putten and Joost N. Kok. Aan de slag met datamining. Praktijkgids Bedrijfsinformatiesystemen. Wolters Kluwer Ten Hagen Stam, The Hague, April 1999. 
[zipped postscript 441K]

Peter van der Putten and Adri van der Wurff. De invoering van database marketing systemen: data mining als twistpunt. CustomerBase Jaarboek '99, December 1998. 
[zipped postscript 130K]

Peter van der Putten. Hoe gaat data mining volwassen worden. CustomerBase, December 1997.

E. Wagenaar. Data Mining in Marketing Databases. In cooperation with P. van der Putten en M. den Uyl. Executive Report DMSA,  October 1997. In Dutch. 
[zipped postscript 388K]

 

Teaching

Student Projects

Current & future projects:

  • Dejan Radosavljevik, PhD candidate (external, T Mobile)
  • Hafeez Osman, PhD candidate, with Michel Chaudron
  • Bernd Dudzik. MSc Media Technology.
  • Paul Kasteleyn. MSc Media Technology.
  • Jorrit Siebelink. MSc Media Technology.
  • Hadiss Yousefi. MSc Media Technology.
Past projects:
  • Andrés Pardo Rodríguez (2014).Say Cheese! Taking Pictures in the Rijksmuseum. MSc Media Technology.First supervisor with G.J. Nauta.
  • Guido Huijser (2014). The Relation between Expectations and Appraisal in Music Discovery driven by Music-related Imagery. MSc Media Technology. First supervisor with Maarten Lamers.
  • Mohammad R. Alaeikhanehshir (2014). Business Intelligence Improvement. Second supervisor with Hans LeFever.
  • Arne Boon (2014). Forgetick:Reminding to Forget in Digital Culture. MSc Media Technology. First Supervisor with Bas Haring.
  • Rosen Bogdanov (2013), Human Plant Interaction. MSc Media Technology.
  • Ricardo Blikman (2013). Ranking of Multi Word Terms. MSc ICT in Business. Second supervisor, with Joost Kok.
  • Seher Altinay (2013). Data Quality Management: A Solvency II Perspective. MSc ICT in Business, first supervisor, with Emiel Caron.
  • Palupi Kusuma (2013). Extending traditional telecom churn prediction using social network data. First supervisor, with Frank Takes and Dejan Radosavljevik.
  • Irna Wahyuni (2013). Providing Mobile Money to Unbanked Customers. MSc ICT in Business, first supervisor, with Hans LeFever.
  • Ana Isabel Loureiro (2013). Quantitative evaluation of clustering: an application to the banking sector. Second supervisor, with Carlos Soares (University of Porto)
  • Jonathan Masey (2012). A conceptual model: Identifying the drivers of pricing elasticity in Electronics. MSc ICT in Business. First supervisor, with Michel Chaudron.
  • Martin Illiev (2012): "A Method for Automated Prediction of Defect Severity Using Ontologies". MSc Computer Science, second supervisor with Michel Chaudron.
  • Palupi Kusuma (2012). Mobile Data Usage Pattern Mining. Science Based Business internship at T-Mobile, with Dejan Radosavljevik.
  • Polly Oskam, Martin Weber, Erik Jansen (2012): Coach Media Technology Semester project 50 Per Cent - Mid Life
  • Berend Nordeman (2012): "Data Storage on Paper", MSc Media Technology, first supervisor with Maarten Lamers.
  • Adrian Kentsch (2011): "Exploratory Recommendations Using Wikipedia's Linking Structure", second supervisor with Walter Kosters and Frank Takes.
  • Dejan Radosavljevik (2009): "Prepaid Churn Modeling Using Customer Experience Management Key Performance Indicators", second supervisor with Hans Borgman and Kim K. Larsen.
  • Zhen Ni (2007): "Recommendations for an Improved Transactional Forecasting Tool Model in ABN AMRO". MSc ICT in Business, first supervisor with Thomas Baeck, Maaike Lycklama a Nijeholt and ABN AMRO.
  • Ning Xu (2007): Explanation Interfaces in Recommender Systems. MSc ICT in Business, first supervisor with Walter Kosters.
  • Lei Tao (2006): "Using Genetic Programming to Find Optimal Purchase-Ordering Rules". MSc ICT in Business, second supervisor with Thomas Baeck.
  • Bastiaan Maat (2006): "The Need For Fusing Head & Neck Cancer Data. Can More Data Provide A Better Data Mining Model For Predicting Survivability Of Head & Neck Cancer Patients?". MSc ICT in Business, first supervisor, with Walter Kosters and Leiden University Medical Center.
  • Thijs van Starkenburg (2006): "Improving cancer survivability prognostication software: Experiments with the World Wide Web, Neural Networks and Data mining." MSc Computer science, second supervisor, with Joost Kok and Leiden University Medical Center.
  • Gong Chao (2006): "Simulation and Optimization in Analytical and Collaborative Customer Relationship Management". MSc ICT in Business, first supervisor, with Walter Kosters and Chordiant Software.
  • Rui Chen (2006): "Application of Collaborative Filtering Algorithm in Bioinformatics". MSc ICT in Business, first supervisor, with Walter Kosters.
  • Menno Israel (2006): "Visual Scene Classification." MSc Cognitive Science, Radboud Universiteit Nijmegen, company supervisor, with Egon van den Broek.
  • Zhaochun Sun (2005): "EQPD, A Way to Improve the Accuracy of Mining Fused Data?". MSc ICT in Business, first supervisor, with Walter Kosters.
  • Sergio Prieto Ballons (2005): "Crime Data Mining: An Overview and Applications". MSc ICT in Business, first supervisor, with Walter Kosters and Sentient Information Systems.
  • Lina Sun (2005): "Making the right offer to the right customer: strategies for real world multi product decisions". MSc ICT in Business, first supervisor, with Walter Kosters.
  • Daniel van Hilten en Wouter Volkeri (2005): "What is the impact of cultural differences on multi-site software development?". MSc ICT in Business, second supervisor, with Hans Borgman and an Enterprise Software Vendor.
  • Wei Zhang (2005): "Evolving Technical Trading Rules with a Hybrid Genetic Programming and Evolution Strategies Approach". MSc ICT in Business, second Supervisor, with Thomas Baeck.
  • Jinshuo Liu (2005): "Shape Analysis & Pattern Recognition of the Pathogen Yeast Crytococcus neoformans Using Image". MSc Computer Science, Second supervisor, with Fons Verbeek.
  • Zan Li & Tiang Feng (2005): "Outdoor Image Orientation on the basis of Neural Networks." Project study Computer Science, second supervisor with Nies Huijsmans
  • Ling Jun Meng (2004): "Artificial Immune System for Knowledge Discovery". MSc ICT in Business, first supervisor, with Walter Kosters.
  • Xander van Pelt (2001): A Constrained Data Fusion Approach. MSc. Thesis, Computer Science. company supervisor, with Walter Kosters and Sentient Machine Research.
  • Martijn Ramaekers (2000): M. Ramaekers, Een procesmodel voor Data Fusie. Internship Bedrijfsinformatietechnology University of Twente, company supervisor, with Maurice van Keulen and Sentient Machine Research
  • Irene Matzken (2000): "Evaluation of the Vicar Video Navigator", project study Computer Science, company supervisor, Sentient Machine Resarch.
  • Michel de Ruiter (1999): "Bayesian classification in data mining: theory and practice." MSc. Thesis, BWI, Free University of Amsterdam, company supervisor, with Wojtek Kowlaczy and Sentient Machine Research.
  • Roelien van Waas (1999), "A Secure Electronic Marketplace with Matching facilities: a framework for a SEMM++-application", MSc Cognitive Science and Engineering, company supervisor Sentient Machine Research.
  • Pascal Wijbenga (1998): "Parseren van autoadvertenties", MSc Computer Science Nijmegen University, company supervisor Sentient Machine Research

Program Committees and Reviewing

  • KDD '15 Research Track
  • KDD '14 Industry Track
  • ECML PKDD '14
  • Benelearn '14
  • BNAIC '14
  • Editorial board, Journal of Marketing Analytics
  • KDD '13 Industry Track, Industrial Track best paper committee
  • BNAIC '13
  • Benelearn '13
  • CIKM '13
  • 2013 IEEE International Conference on Big Data (IEEE BigData 2013)
  • Demo track, ECML/PKDD ´13. Also sponsor chair for ECML/PKDD '13.
  • BNAIC '12
  • Demo track, ECML/PKDD ´12
  • KDD '12 Industry Track
  • Special Session on Machine Learning for Business of the International Joint Conference on Neural Networks. Brisbane, Australia. June 10-15, 2012.
  • Benelearn '12
  • IS-MiS 2012: Management Intelligent Systems
  • Data Mining Case Studies Workshop and Practice Prize (DMCS '11) at ICDM '11. , Vancouver, Canada. December 11-14, 2011.
  • Benelearn-2011, May 20 in The Hague.(Organizer)
  • BNAIC '11
  • KDD '11 Industrial Track.
  • BNAIC '10 Research Track, Luxembourg, October 25-26, 2010.
  • KDD '10 Industrial Track, Washington DC, July 25-28, 2010.Member industry/Government Best Paper and Practice Prize award committee.
  • BNAIC '09 Research Track and BNAIC '09 Industry Track. Invited Talk Industry Track. Eindhoven, The Netherlands. 29-30 October, 2009
  • ECML/PKDD '09. Bled, Slovenia. September 7-11, 2009
  • Data Mining Case Studies (DMCS '09), European Co Chair, workshop at KDD '09, Paris, France. June 28, 2009
  • BNAIC '08. Enschede, The Netherlands. October 30-21, 2008
  • KDD '08 Workshop on Data mining for Business Applications. Las Vegas, August 24, 2008
  • BNAIC '07. Utrecht, The Netherlands, November 5-6, 2007
  • ECML/PAKDD '07 workshop 'Data Mining for Business', Nanjing, China, 22-25 May 2007
  • ECML06/PKDD '06 workshop PRACTICAL DATA MINING: Applications, Experiences and Challenges, Berlin, Sept 18-22
  • KDD '06 Workshop on Data mining for Business Applications, August 20 2006 Philadelphia PA
  • ICSC Symposium on Advanced Computing in Financial Markets, at ICSC Congress on Computational Intelligence Methods and Applications (CIMA'2005). Istanbul, Turkey, December 15-17 2005
  • ECML/PKDD2005. Data Mining for Business.Porto, Portugal, Oct 3-7 2005
Reviewing for a variety of journals including Decision Support Systems (Elsevier), Computational Statistics and Data Analysis (CSDA, Elsevier), Biomedical Signal Processing and Control, Computer Methods and Programs in Biomedicine (Elsevier), Information Fusion (Elsevier)

Selected Events

From this list of events I visited (or will) you might be able to predict ;-) where to meet me:

(*=talk or paper)

Contact Info

This website is under development. Mail me if you have any questions (mailto:pvdputten-at-hotmail.com)