David Martens.

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1 David Martens Professional experience Since 2008 Katholieke Universiteit Leuven Post-doctoral researcher (FWO) Substitute Lecturer Management Informatics Department Hogeschool Gent Lecturer Member Academization Committee Faculty of Business Administration and Public Administration Katholieke Universiteit Leuven Research assistant Management Informatics Department 2004 KPMG Junior Advisor Internship KPMG, Information Risk Management Business continuity management program development for KPMG Education PhD in Applied Economic Sciences Building Acceptable Classification Models for Financial Engineering Applications Management Informatics Department Katholieke Universiteit Leuven Supervisors: Bart Baesens, Jan Vanthienen (Katholieke Universiteit Leuven) External committee members: Tony Van Gestel (Dexia Group), Thomas Stützle (U.L.B.), Foster Provost (New York University), Dolores Romero-Morales (Oxford University) Finalist of ACM SIGKDD doctoral dissertation award Master of Business Administration Reims Management School (Reims, France) Fairleigh Dickinson University (New Jersey, USA) Graduated top 5 with 78 % Civil Engineer in Computer Science Katholieke Universiteit Leuven Graduated cum laude with 76 % Thesis: A comparative study of educational timetabling techniques 1

2 Expertise Business Intelligence: Data Mining, Knowledge Management, Decision Support Systems Application areas: credit scoring, churn prediction, software mining, audit mining Programming Languages: Matlab, Java, C/C++, Prolog, Haskell, SAS Teaching Experience Knowledge Management Strategic Management & New Technologies Business Cases Faculty of Business Administration and Public Administration, Hogeschool Gent, 2008 Knowledge Discovery in Data - yearly lessons from the graduate course Business Intelligence, Commercial Engineers, K.U.Leuven, May Data Mining - Searching for knowledge in your data - 4 day course for professionals at University Center for Statistics (UCS), K.U.Leuven, April 2006, 2008 Predictive Analytics and Data Mining - 1 day course for professionals at OR Society, Birmingham, United Kingdom, April 2008 Applications of Ant Colony Optimization - lesson from the graduate course Multi-Agent Systems, Civil Engineers in Computer Science, K.U.Leuven, March 2008 Academic Organizational Activities Guest editor, together with Tom Fawcett and Bart Baesens Special Issue on Swarm Intelligence for Knowledge Discovery in Data, for the international journal Machine Learning (SCI 2006: 2.654), 2008 Organizer Workshop on New Frontiers in Data Mining, January 9th 2008 Program Committee Member The Sixth International Workshop on Ant Colony Optimization and Swarm Intelligence, Brussels (Belgium), September The Second International Workshop on Nature Inspired Cooperative Strategies for Optimization, Acireale (Italy), November The Second International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2007), Zhengzhou (China), September Session Chair Artificial Intelligence and Neural Networks, 21st European Conference on Operational Research, Reykjavik (Iceland), July 4th 2006 Project Grants: Proposal Involvement OT: Project on Process Intelligence (2008) FWO: Projects on Data Mining (2007, 2008), Basel II (2007) and Process Intelligence (2008) 2

3 Extra-curricular Activities Student union Reuzegom: president ( ) Umbrella student union Senioren Konvent: vice-president ( ) Squash, Skiing, Traveling Ad Hoc Reviewing Annals of Information Systems Applied Soft Computing European Journal of Operational Research IEEE Transactions on Evolutionary Computation IEEE Transactions on Systems, Man and Cybernetics - Part B IEEE Transactions on Systems, Man and Cybernetics - Part C Journal of Information Science Journal of Operational Research Society Neurocomputing New Mathematics and Natural Computation Soft Computing Publication List Up-to-date publication list available online at: International journal publications Accepted for publication Gerd Castermans, David Martens, Tony Van Gestel, Bart Hamers, Bart Baesens An Overview and Framework for PD Backtesting and Benchmarking Journal of the Operational Research Society SCI 2008: David Martens, Bart Baesens, Building Acceptable Classification Models, Annals of Information Systems SCI 2008: David Martens, Tony Van Gestel, Manu De Backer, Raf Haesen, Jan Vanthienen, Christophe Mues, Bart Baesens, Credit Risk Management Using Ant Colony Optimization, Journal of the Operational Research Society SCI 2008: Published Stijn Goedertier, David Martens, Jan Vanthienen, Bart Baesens Robust Process Discovery with Artificial Negative Events Journal of Machine Learning Research SCI 2008: Bart Baesens, Christophe Mues, David Martens, Jan Vanthienen, 50 years of Data Mining and OR: upcoming trends and challenges, Journal of the Operational Research Society, Vol. 60, Nb. S1, pp. S16-S23, 2009 SCI 2008: Bjorn Cumps, David Martens, Manu De Backer, Stijn Viaene, Guido Dedene, Raf Haesen, Monique Snoeck, Bart Baesens Inferring Rules for Business/ICT alignment using Ants, Information and Management, Vol. 46, Nb. 2, pp , 2009 SCI 2008:

4 David Martens, Building Acceptable Classification Models for Financial Engineering Applications SIGKDD Explorations Vol. 10, Nb. 2, pp. 30-3, December 2008 SCI 2007: David Martens, Bart Baesens, Tony Van Gestel, Decompositional Rule Extraction from Support Vector Machines by Active Learning, IEEE Transactions on Data and Knowledge Engineering Vol. 21, Nb. 1, pp , 2009 SCI 2008: David Martens, Liesbeth Bruynseels, Bart Baesens, Marleen Willekens, Jan Vanthienen, Predicting Going Concern Opinion with Data Mining, Decision Support Systems Vol. 45, pp SCI 2008: Olivier Vandecruys, David Martens, Bart Baesens, Christophe Mues, Manu De Backer, Raf Haesen, Mining Software Repositories for Comprehensible Software Fault Prediction Models Journal of Systems and Software Vol. 81, Nb. 5, pp , 2008 SCI 2008: Sijn Goedertier, David Martens, Bart Baesens, Raf Haesen, Jan Vanthienen, Process mining as first-order classification learning on logs with negative events, Lecture Notes in Computer Science, no. Proceedings of the third Workshop on Business Process Intelligence (BPI 07), Lecture Notes In Computer Science, Springer, Brisbane, Australia, September 25-27, 2007 SCI 2008: David Martens, Manu De Backer, Raf Haesen, Jan Vanthienen, Monique Snoeck, Bart Baesens, Classification with Ant Colony Optimization, IEEE Transactions on Evolutionary Computation, Vol. 11, Nb. 5, pp , 2007 SCI 2008: Paper most frequently accessed in October 2007 Tony Van Gestel, David Martens, Daniel Feremans, Bart Baesens, Johan Huysmans, Jan Vanthienen, Forecasting and Analyzing Insurance Companies Ratings, International Journal of Forecasting, Vol. 23, Nb. 3, pp , 2007 SCI 2008: David Martens, Bart Baesens, Tony Van Gestel, Jan Vanthienen, Comprehensible Credit Scoring Models Using Rule Extraction From Support Vector Machines, European Journal of Operational Research, Vol. 183, Nb. 3, pp , 2007 SCI 2008: David Martens, Manu De Backer, Raf Haesen, Bart Baesens, Christophe Mues, Jan Vanthienen, Ant-Based Approach to the Knowledge Fusion Problem Lecture Notes in Computer Science, ANTS Workshop 2006, Brussels (Belgium), pp , September 2006 SCI 2005: Johan Huysmans, David Martens, Bart Baesens, Jan Vanthienen, Country Corruption Analysis with Self Organizing Maps and Support Vector Machines Lecture Notes in Computer Science, PAKDD WISI Workshop, Signapore, 2006 SCI 2005: Manu De Backer, Raf Haesen, David Martens, Bart Baesens, A Stigmergy Based Approach to Data Mining Lecture Notes in Computer Science, The 18th Australian Joint Conference on Artificial Intelligence (AI 2005), Sydney (Australia), pp , December 2005 SCI 2005: Johan Huysmans, Bart Baesens, David Martens, Katrien Denys, Jan Vanthienen, New Trends in Data Mining Tijdschrift voor Economie en Management, Vol. L, pp , September 2005 Books David Martens, Building Acceptable Classification Models for Financial Engineering Applications, PhD text, pp. 247, KULeuven,

5 Contributions to books David Martens, Johan Huysmans, Rudy Setiono, Jan Vanthienen, Bart Baesens, Rule Extraction from Support Vector Machines: An Overview of Issues and Application in Credit Scoring, Rule Extraction from Support Vector Machines, Studies in Computational Intelligence, Vol. 80, Springer, pp , 2008 David Martens, Manu De Backer, Raf Haesen, Bart Baesens, Tom Holvoet, Ants Building Rule- Based Classifiers, Swarm Intelligence and Data Mining, Studies in Computational Intelligence, Vol. 34, Springer, pp , 2006 Dutch publications David Martens, Kennis vinden zonder te zoeken?, Datanews, May 2008 David Martens, Mieren voorspellen de toekomst, IT Professional, pp , April 2008 Bart Baesens, David Martens, ICT uitdagingen in het Basel II tijdperk, Informatie, pp , Maart 2008 David Martens, Raf Haesen, Manu De Backer, Bart Baesens, Artificile Mieren en Hun Zoektocht Naar Kennis, Informatie, pp , Mei 2006 Raf Haesen, David Martens, Manu De Backer, Bart Baesens, AntMiner+: Een systeem van kennis-ontginnende mieren, Business InZicht, Nummer 20, November 2005 David Martens, Trend - Data Mining, Informatie, pp. 8-9, December 2005 Presentations at International Conferences Applications for Classifications: Key Success Factors and New Domains, OKDD 2008 Workshop on Data Mining for Business Applications, Las Vegas (U.S.), August 24th 2008 Active learning for SVM rule extraction, Operational Research Conference 50, York (U.K.), September 10th 2008 An Overview and Framework for PD Backtesting and Benchmarking, Credit Scoring and Credit Control X, Edinburgh (U.K.), July 30th 2007 Placing Process Intelligence within the Business Intelligence Framework, Sixth International Conference on Information and Management Sciences, Lhasa, Tibet (China), July 3rd 2007 Ant-Based Approach to the Knowledge Fusion Problem, Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006, Brussels (Belgium), September 5th 2006 Measuring the consistency with prior knowledge of classification models, Operational Research Conference 48, Bath (U.K.), September 11th 2006 Building Acceptable Classifiers with Ants, invited speaker in Artificial Intelligence and Neural Networks Stream, 21st European Conference on Operational Research, Reykjavik (Iceland), July 4th 2006 A Stigmergy Based Approach to Data Mining, The 18th Australian Joint Conference on Artificial Intelligence (AI 2005), Sydney (Australia), December 7th

6 On the Use of Ant Systems for Data Mining, Operational Research Conference 47, Chester (U.K.), September 15th 2005 Adding Comprehensibility to Support Vector Machine Models Using Rule Extraction Techniques, Poster presentation at Credit Scoring and Credit Control IX, Edinburgh (U.K.), September 8th 2005 Benchmarking State-of-the-art Classification Techniques for Credit Scoring, International Symposium on Applied Stochastic Models and Data Analysis, Brest (France), May 20th 2005 Seminar Presentations Business Applications of New Classification Techniques, Workshop on New Frontiers in Data Mining, 9 January 2008 Building Acceptable Classification Models for Financial Engineering Applications, PhD defense, KULeuven, 8 January 2008 Building Acceptable Classification Models for Financial Engineering Applications, 2nd doctoral seminar, LIRIS, KULeuven, 17 September 2007 Data Mining with Ant Colony Algorithms: Theory and Applications, CORMSIS seminar, University of Southampton, 13 February 2007 Building Acceptable Classification Models for Financial Engineering Applications, 1st doctoral seminar, LIRIS, KULeuven, 15 September 2006 Building Rule-Based Classifiers with Ant Colony Optimization, IRIDIA seminar, ULB Brussels, 24 March 2006 Research Reports Stijn Goedertier, David Martens, Bart Baesens, Raf Haesen, Jan Vanthienen, A new approach for discovering business process models from event logs, 20pp. FETEW Research Report KBI 0716, K.U.Leuven 2007 Bjorn Cumps, David Martens, Manu De Backer, Raf Haesen, Stijn Viaene, Guido Dedene, Bart Baesens, Monique Snoeck, Predicting business/ict alignment with AntMiner+, 29pp. FETEW Research Report KBI 0708, K.U.Leuven 2007 David Martens, Bart Baesens, Tony Van Gestel, Jan Vanthienen, Comprehensible credit scoring models using rule extraction from support vector machines, 21pp., Research Report 0581, Dept. of Decision Sciences and Information Management, K.U.Leuven 2005 In The Press Virtuele mieren voorspellen kredietwaardigheid, De Standaard, 19/01/2008 Onderzoeker voorspelt kredietwaardigheid met virtuele mieren, Het Laatste Nieuws, 18/01/2008 Onderzoeker voorspelt kredietwaardigheid met virtuele mieren, De Morgen, 18/01/2008 Mieren zoeken wanbetalers, Het Nieuwsblad, 23/01/2008 6

7 Mieren in een Bank, Knack, 27/02/2008 Radio interview on Radio 1, Feyten of Filet, 18/01/2008 Mieren waarschuwen voor wanbetalers, ROB (regional news of Vlaams-Brabant), 18/01/2008 Mieren waarschuwen voor wanbetalers, Campuskrant, K.U.Leuven, 13/02/2008 7

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