Curriculum Vitae Bart Baesens - KU Leuven · Curriculum Vitae B. Baesens 3 I was a member of the program committee of the Eighth International Conference on Enterprise Information

Curriculum Vitae Bart Baesens

Personal data

Surname: Baesens

First Name: Bart Maurice Marcella

Nationality: Belgian

Date of Birth: February 27th, 1975

Place of Birth: Bruges, Belgium

Marital Status: married to Katrien Denys

Children Ann-Sophie (born: April 4th, 2005);

Victor (born: August 23rd, 2006)

Hannelore (born: August 11nd, 2008)

Work addresses:

Department of Decision Sciences and Information Management

KU Leuven

Naamsestraat 69

B-3000 Leuven

Belgium

Tel.: +3216326884

Fax: +3216326732

E-mail: [email protected]

School of Management

University of Southampton

Southampton

SO17 1BJ

United Kingdom

E-mail: [email protected]

Home address:

Groddeweg 12

B-3010 Kessel-Lo

Belgium

Tel./Fax: +3216292191

Mobile: +32486948656

Current Profession

Associate professor

Department of Decision Sciences and Information Management

KU Leuven

Lecturer in Management Science (assistant professor)

School of Management

University of Southampton

mailto:[email protected]

Curriculum Vitae B. Baesens 2

Research Expertise

I consider myself to be an applied researcher, where I have used both quantitative research

methods, as well as qualitative research methods. My key research interests have been in

credit scoring, Basel II, customer relationship management (CRM), information systems,

business intelligence, business rules, customer scoring and decision support systems. My

interest in business intelligence (BI) and machine learning has allowed me to keep foot into

the basic research side of BI (mainly computer science) and the applied BI side (mainly the

business and management information systems communities). Part of what I observed was

a gap between the practitioner and the academician in the BI field. In trying to bridge this

gap, I have collaborated with several companies. This research has resulted in a number of

publications in high-quality journals and/or conferences. I have also obtained a number of

best-speaker awards when presenting my key findings (cf. infra). I am also regularly invited

to organize courses, seminars and/or special sessions on business intelligence for international

conferences or universities.

Organizational Activities

I am the secretary and member of the board of directors of the VZW Contactgroep

Beleidsinformatica (CBL) since December 2000.

Together with the University Center for Statistics at the KU Leuven, Belgium, I organized

and planned the course “Data Mining: Searching for Knowledge in Your Data” which took

place on January, 14th, 15th, 17th, 21st, 22th, 24th, 2002 and was repeated on September, 3th, 5th,

9th, 10th, 2002.

I am a member of the SAS Belgium and Luxembourg Users Group (BLUES) Committee

since October 24th, 2002.

Together with my former supervisor, prof. dr. Jan Vanthienen we organized the Credit

Scoring Workshop at the KU Leuven, Belgium, on March 11th, 2003 and September 25th,

2003.

I organized a special session on Data Analysis for the Eighth Online World Conference on

Soft Computing in Industrial Applications, September 29th – October 10th, 2003.

I co-chaired a session on classification and data mining for the Fifth International FLINS

Conference on Computational Intelligent Systems for Applied Research (FLINS’2002) in

Ghent, Belgium.

I chaired a session on artificial intelligence and decision support systems for the Fifth

International Conference on Enterprise Information Systems (ICEIS’2003) in Angers,

France.

I organized a special session on Data Analysis for the Ninth Online World Conference on

Soft Computing in Industrial Applications, September 20th – October 8th, 2004.

I was a member of the program committee of the Seventh International Conference on

Enterprise Information Systems (ICEIS’2005).

I organized the workshop on Credit Scoring and Basel II for the Studiecentrum voor

Automatische Informatieverwerking (SAI) which took place in the Sodehotel, Woluwe, on

October 18th, 2004.

I organized a special session on data mining for the OR47 Conference, September 13th-15th

2005, Chester, United Kingdom, 2005.


I was a member of the program committee of the Eighth International Conference on

Enterprise Information Systems (ICEIS’2006), 23rd-27th May, 2006, Paphos, Cyprus.

I was a member of the program committee of the Tenth Online World Conference on Soft

Computing in Industrial Applications (WSC10), September 19th - October 7th, 2005.

Together with prof. dr. Lyn Thomas and dr. ir. Tony Van Gestel, I organized the Infoline

workshop Validating & Stress testing Retail Portfolios, which took place in London,

United Kingdom, September 12th, 2005.

Together with prof. dr. Lyn Thomas, prof. Jonathan Crook and the OR Society (ORS), I

organized the course Introduction to Credit and Behavioural Scoring, which took place in

Birmingham, United Kingdom, October 12th, 2005.

I was a member of the program committee of the 2006 International Conference on Data

Mining (DMIN’06) which is part of the 2006 World Congress in Computer Sciences, June

26-29, 2006 Las Vegas, Nevada, USA.

Together with prof. dr. Lyn Thomas and dr. ir. Tony Van Gestel, I organized a workshop

Validating & Stress testing Retail Portfolios, which took place in Tervuren, Belgium,

February 6th, 2006.

I was the program director for the BSc Management Science, School of Management,

University of Southampton, during 2005-2006.

I was a member of the program committee of the 2007 International Conference on

Enterprise Information Systems and Web Technologies (EISWT-07) organized during 9-

12 July 2007 in Orlando, FL, USA.

I co-organized the Workshop on Basel II and Credit Risk Modelling in Consumer

Lending which took place in Southampton, September 6-8 2006 (together with Lyn Thomas,

David Hand, Jonathan Crook).

I was a member of the program committee of Ninth International Conference on

Enterprise Information Systems (ICEIS 2007), 12-16 June 2007, Funchal, Madeira,

Portugal.

I am a member of the program committee of Tenth International Conference on Enterprise

Information Systems (ICEIS 2008), 12-16 June 2008, Barcelona, Spain.

I organized the workshop Frontiers in Data Mining, which took place on January 9th, 2008

in Leuven, Belgium.

I am a member of the program committee of ANTS 2008 - Sixth International Workshop

on Ant Colony Optimization and Swarm Intelligence, to be held in Brussels, Belgium,

September 22-24, 2008.

I am a member of the program committee of ICAART-2009 - International Conference on

Agents and Artificial Intelligence; to be held in Porto, Portugal, January 19-21, 2009.

I am a member of the program committee for the Data Mining for Business Applications

Workshop, 14th ACM SIGKDD International Conference on Knowledge Discovery & Data

Mining, August 24, 2008.

I am a member of the program committee for the ninth Industrial Conference on Data

Mining, July 20-22, 2009, Leipzig, Germany.

I am a member of the program committee for the KDIR 2011 - International Conference on

Knowledge Discovery and Information Retrieval, October 26-29, 2011, Paris, France.


I am a member of the program committee for the ECML-PKDD 2012 Conference,

September 24-28, 2012, Bristol, United Kingdom.

I co-organised a session on Network Mining and Analysis for the 54th Annual Conference

of the UK Operational Research Society (OR54), Edinburgh, UK, September 4–6, 2012.


TRODUCTION TO CREDIT AND BEHAVIOURAL SCORIN

Phd Supervision

Supervisor or co-supervisor:

David Martens, Building Acceptable Classification Models for Financial Engineering

Applications, LIRIS, Faculty of Economic and Applied Economic Sciences, KU

Leuven, January 8th, 2008.

Elen Lima, Customer Lifetime Value Estimation, School of Management, University

of Southampton, November 28th, 2008.

Nicolas Glady, Customer Lifetime Value Modeling, Faculty of Economic and Applied

Economic Sciences, KU Leuven (together with Christophe Croux), December 8th,

2008.

Elisabeth Van Laere, Capital Regulation of Financial Institutions, the Role of Ratings

and the Tension Field between Regulation and Economic Reality, Faculty of Business

and Economics, KU Leuven, January 26th, 2011.

Wouter Verbeke, Profit Driven Data Mining in Massive Customer Networks: New

Insights and Algorithms, Faculty of Business and Economics, KU Leuven, January

20th, 2012.

Karel Dejaeger, Essays on Empirical Software Engineering, Faculty of Business and

Economics, December 5th, 2012, KU Leuven.

Jochen De Weerdt, Business Process Discovery: New Techniques and Applications,

Faculty of Business and Economics, KU Leuven, October 23rd, 2012.

Filip Caron, Business Process Analytics for Enterprise Risk management and

Auditing, May 27th, 2013.

Thomas Verbraken, Business-Oriented Data Analytics: Theory and Case Studies,

Faculty of Business and Economics, KU Leuven, September 12th, 2013.

Philippe Louis, Case Studies in Quantitative Financial Modeling, Faculty of Business

and Economics, KU Leuven, November 14th, 2013.

Helen Moges, Data Quality for Credit Risk Management, Faculty of Business and

Economics, KU Leuven.

Seppe Vanden Broucke, Business Process Mining, Faculty of Business and

Economics, KU Leuven.

Member of the PhD Examination Committee:

Geert Verstraeten, Issues in Predictive Modelling of Individual Customer Behavior:

Applications in Targeted Marketing and Consumer Credit Scoring, Faculteit

Economie en Bedrijfskunde, Universiteit Gent, December 22nd, 2005 (principal

advisor: Dirk Van den Poel).

Yvonne Seow, Using Adaptive Learning in Credit Scoring to Estimate Acceptance

Probability Distribution, School of Management, University of Southampton, April

25th, 2006 (principal advisor: Lyn Thomas).


Johan Huysmans, Knowledge discovery for customer scoring using neural networks

and support vector machines, LIRIS, Faculty of Economic and Applied Economic

Sciences, KU Leuven, June 13th, 2007 (principal advisor: Jan Vanthienen).

Jia Ni, Using Proteomics Signatures for Early Diagnosis of Ovarian Cancer, School

of Mathematics, University of Southampton, June 28th, 2007 (principal advisor: Julia

Bennell, Chris Potts, Lyn Thomas)

Vink Dennis, Primary Market Spreads of Asset Securitization Issues: Empirical

Investigation and Analysis, Nyenrode Business University, the Netherlands, July 6th,

2007 (principal advisor: André Thibeault).

Stijn Goedertier, Declarative BPM: On the Role of Business Rules in the BPMN Life

Cycle, LIRIS, Faculty of Economic and Applied Economic Sciences, KU Leuven,

September 16th, 2008 (principal advisor: Jan Vanthienen)

Jie Zhang, Survival Analysis for LGD Modeling, University of Southampton,

December 15th, 2010 (principal advisor: Lyn Thomas)

Dirk Thorleuchter, Essays on Text Mining for Improved Decision Making, Ghent

University, February 3rd, 2011 (principal advisor: prof. dr. Dirk Van den Poel)

Philippe Baecke, Essays on Data-Augmentation: the Value of Additional Information,

Faculty of Economics and Business Administration, Universiteit Gent, September 21st,

2012 (principal advisor: Dirk Van den Poel)

Cristián Bravo, Methods for Consumer Credit Risk Modelling Based on Data Mining

and Game Theory, Facultad de Ciencias Físicas y Matemáticas, Universidad de Chile,

December 4th, 2012 (principal advisor: Richard Weber).

Katarzyna Helena Bijak, Selected Modeling Problems in Credit Scoring, University of

Southampton, July 16th, 2013 (principal advisor: Lyn Thomas)

Research Grants

I received the following research projects and grants:

Flemish Fund for Scientific Research (FWO), project G.0615.05, Using business

intelligence techniques for risk profiling of economic entities, 01/01/2005-31/12/2008

(together with prof. dr. Jan Vanthienen).

NBB (National Bank of Belgium), Developing and validating risk models for Basel II,

25.000 Euro (together with prof. dr. Jan Vanthienen).

ING prime foundation partnership together with Vlerick Leuven Gent Management

School, Economic risk and capital allocation, 75.000 Euro per year (37.500 Euro for

research) per year, 01/01/2006-31/12/2008.

School of Management, University of Southampton, pump-priming grant, Studying

the utility of decision tables and diagrams as a graphical knowledge visualisation,

2.000 £ (together with dr. Christophe Mues)

School of Management, University of Southampton, pump-priming grant,

Developing and validating risk models in the context of Basel, 1.000 £ (together with

dr. Christophe Mues)


Fair Isaac, Collection Process Modelling for LGD, 50.000 US $ (together with prof.

dr. Lyn Thomas and dr. Christophe Mues)

SAS, 5.000£ (together with prof. dr. Lyn Thomas and dr. Christophe Mues)

EPSRC Mathematics Case Project - 016/007, Basel II-Compliant Credit Risk

Modelling for Low-Default Portfolios, in collaboration with SAS UK, £ 80,300

(EPSRC: £ 62,300; SAS: £ 18,000) (together with: prof. Lyn Thomas and dr.

Christophe Mues)

NBB (National Bank of Belgium), Evaluating the Compliance and Flexibility of

Service oriented Information Architectures, 25.000 Euro (together with prof. dr. Jan

Vanthienen, prof. dr. Wilfried Lemahieu, prof. dr. Gerd Van den Eede)

NBB (National Bank of Belgium) project entitled, Evaluating the Business Value of

Software Services, 25.000 Euro (together with prof. dr. Monique Snoeck, prof. dr.

Koen Millis)

Flemish Fund for Scientific Research (FWO), G.0915.09, Odysseus project,

Intelligent Information Systems: New Techniques and Applications, 01/07/2008 -

30/06/2013, 100.000 Euro per year for 5 years, total: 500.000 Euro.

Bilateral scientific corporation, KU Leuven - Tsinghua University (Beijing, China),

Intelligent Resource Planning systems, 01/01/2009-01/01/2011, 50.000 Euro (together

with: Jan Vanthienen, Nico Vandaele, Marc Lambrecht, Inneke Van Nieuwenhuyse,

Chen Quoqing, Chen Jian)

Graydon Prime Foundation Partnership, together with Vlerick Leuven Gent

Management School, Graydon Institute of Risk & Opportunity Scoring, 75.000 Euro

per year (37.500 Euro for research), 1/01/2009-31/12/2011.

NBB (National Bank of Belgium), Backtesting en Benchmarking van krediet risico

modellen na 2008: een SOA gebaseerde informatiesysteem architectuur, 34.940 Euro

(together with prof. dr. Jan Vanthienen and prof. dr. Stephan Poelmans).

Academic Research Fund Flemish Government, Rating banks: a myth resolved,

41.800 Euro (together with prof. A. Thibeault, E. Van Laere).

NBB (National Bank of Belgium), NBB/10/006, Network models for Credit Risk

Analysis, 20.270 Euro (together with prof. dr. Jan Vanthienen and prof. dr. Stephan

Poelmans).

Academic Research Fund, On the Subjectivity of Bank Ratings, 45.600 Euro

(together with prof. A. Thibeault, E. Van Laere).

KU Leuven, Onderzoekstoelage (OT), OT/10/010, Nieuwe technieken en metrieken

voor ontginning van bedrijfsprocessen, 01/10/2010-30/09/2014, 300.000 Euro

(together with prof. dr. Jan Vanthienen).

NBB (National Bank of Belgium), NBB/11/004, Holistische

kredietrisicomodellering: innovatieve modellen, nieuwe inzichten en baanbrekende

toepassingen, 46.800 Euro (together with professor Lieven De Moor).

IBM, Intelligent Business Decision Making, 20.000 Euro (together with Jan

Vanthienen, Wilfried Lemahieu).

KU Leuven, BIL11/11, Bilaterale Wetenschappelijke Samenwerking Latijns

Amerika-KU Leuven, Profit driven metrics for a holistic approach to evaluating Data

Mining Models, 10.800 Euro.


KU Leuven, GOA/12/003, Radicale innovatie, competitie, co-operatie en groei,

01.10.2011-30.09.2016, toeleverancier.

FWO, G.0816.12N, Advanced Survival Analysis for Credit Risk Modelling:

innovative techniques, new insights and applications, 244.000 Euro (together with

Gerda Claeskens).

Ticketmatic, Research Chair on Cultural Data Analytics, 01.02.2012-31.01.2015,

150.000 Euro

KU Leuven, BIL11/15T, Bilaterale Samenwerking 2011 Tsinghua University-KU

Leuven, Social Commerce and Business Intelligence Techniques, 67.876 Euro.

Hercules, Economic and Financial databases for top quantitative research in finance,

business and economics, 992.267 Euro (together with M. Willekens, L. Sels)

RSZ, FAIR Research Chair on Forecasting en Network Analytics voor het Beheer van

Inningsrisico’s, 01.10.2012-30.09.2015, 150.000 Euro

KU Leuven, BIL 12/01, Bilaterale Wetenschappelijke Samenwerking Latijns

Amerika-KU Leuven 2012, Development of rule-based classification using profit

maximization, 12.500 Euro.

KU Leuven, BIL 13/01, Bilaterale Wetenschappelijke Samenwerking Latijns

Amerika-KU Leuven 2012, Dynamic Clustering, from an academic approach to a real

business solution: theory and application, 12.500 Euro.

Professional Memberships

I am a member of the following professional organizations: Member of the Stuurgroep van het Universitair Centrum voor Statistiek, KU Leuven,

since 2006.

Member of the Steer Committee of the Data Mining Garden, an industry consortium

on data mining.

Member of the advisory group for the Data News journal

Awards and Nominations

When presenting the results and key findings of my research, I have received the following

awards and nominations.

I received a Best Paper nomination Economic and Financial Systems II at the Fifth World

Multi-Conference on Systemics, Cybernetics and Informatics (SCI'2001), Orlando, Florida,

July, 2001. .

I received a Best Paper nomination at the Fourth International Conference on Enterprise

Information Systems (ICEIS’2002), Ciudad Real, Spain, April, 2002.

I was elected SAS Student Ambassador at SAS SEUGI, Paris, June, 2002.

I received the Best Speaker award at the SAS Academic Day in La Tentation, Brussels, May

23th, 2002.


I received the Best Speaker award at the SAS Belgium & Luxembourg Users (BLUES)

Conference in the Brabanthal, Haasrode, October 24th, 2002.

I received a Best Paper nomination at the Fifth International Conference on Enterprise

Information Systems (ICEIS’2003), Angers, France, April, 2003.

I was the Best Speaker at the seminar Modelling Challenges in the Context of Basel II, SAS,

SAS, Tervuren, April 20th, 2004.

Together with Rudy Setiono and Christophe Mues, we won the Best Paper Award in the

Design Track at the International Conference on Information Systems (ICIS 2006), for our

paper “Risk Management and Regulatory Compliance: A Data Mining Framework Based on

Neural Network Rule Extraction”, December 2006.

We received the McGraw Hill Australia Honourable Mention for Paper in

Entrepreneurship Finance, Profitability & Growth for our paper: VANHOUTTE C.,

MARTENS D., DE WINNE S., SELS L., BAESENS B., The initial resource-performance

relationship in new ventures: Towards a configurational approach, Proceedings of the Seventh

AGSE Conference, Queensland, Australia, February 2-5, 2010.

We received the EURO 2014 award for the best EJOR paper in the category Innovative

Applications for our paper: VERBEKE W., DEJAEGER K, MARTENS D., HUR J., BAESENS B.,

New insights into churn prediction in the telecommunication sector: a profit driven data

mining approach, European Journal of Operational Research, Volume 218, Issue 1, pp. 211-

229, 2012.

Editorship and Ad Hoc Reviewing

I am on the Editorial Board of the following journals:

Machine Learning journal.

IEEE Transactions on Neural Networks and Learning Systems

Journal of Management Science.

Springer book series in Quantitative Management

Tijdschrift Informatie

I co-edited a special issue of the journal Expert Systems with Applications (SCI 2008

Impact Factor: 2.596) on Intelligent Systems for Financial Engineering that appeared in

April 2006.

I co-edited a special issue of the Machine Learning journal (SCI 2008 Impact Factor:

2.326) on Swarm Intelligence for Knowledge Discovery in Data.

I co-edited a special issue of the IEEE Transactions on Neural Networks journal (SCI

2008 Impact Factor: 3.726) on White box non-linear prediction models.

I have done ad-hoc reviewing for the following journals.

Applied Intelligence

Computational Economics


Computers and Operations Research

Decision Support Systems

European Journal of Operational Research

Fuzzy Sets and Systems

IEEE Transactions on Evolutionary Computation

IEEE Transactions on Neural Networks

IEEE Transactions on Systems, Man, and Cybernetics: Part B

IEEE Transactions on Systems, Man, and Cybernetics: Part C

International Journal of Intelligent Systems in Accounting, Finance & Management

Computational Statistics and Data Analysis

Journal of Applied Soft Computing

Journal of Computing

Journal of Futures Markets

Journal of Information Science

Journal of the Operational Research Society

Management Science

Neural Networks

Neurocomputing

Pattern Recognition Letters

I also regularly write book and article reviews for the ACM Computing Reviews journal.

Interviews

B. BAESENS, Reliable credit-risk analysis based on neural networks, Interview in Banking &

Finance, pp. 96-97, March, 2003.

B. BAESENS, Ask the Expert, SAS Com magazine, first quarter, 2008.

B. BAESENS, Kredietmodellen in extreme omstandigheden, Financial Director’s Magazine,

mei 2009.


Publications1

Journal publications

[1] SERET A., VANDEN BROUCKE S., VANTHIENEN J., BAESENS B., A Dynamic

Understanding of Customer Behavior Processes Based on Clustering and Sequence

Mining, Expert Systems with Applications, forthcoming, 2013. SCI 2012 Impact

Factor: 1.854

[2] CARON F., VANDEN BROUCKE S., VANTHIENEN J., BAESENS B., Advanced Rule-Based

Process Analytics: Applications for Risk Response Decisions and Management Control

Activities, Expert Systems with Applications, forthcoming, 2013. SCI 2012 Impact

Factor: 1.854

[3] MINNAERT B., MARTENS D., DE BACKER M., BAESENS B., To Tune or not to Tune: Rule

Evaluation for Metaheuristic-based Sequential Covering Algorithms, Data Mining and

Knowledge Discovery, forthcoming, 2013. SCI 2012 Impact Factor: 2.877

[4] CARON F., VANTHIENEN J., VANHAECHT K., VAN LIMBERGEN E., DE WEERDT J.,

BAESENS B., Monitoring Care Processes in the Gynecologic Oncology Department,

Computers in Biology and Medicine, forthcoming, 2013. SCI 2012 Impact Factor:

1.162

[5] TOBBACK E., MARTENS D., VAN GESTEL T., BAESENS B., Forecasting loss given default

models: impact of account characteristics and the macroeconomic state, Journal of the

Operational Research Society, forthcoming 2013. SCI 2012 Impact Factor: 0.989

[6] VERBEKE W., MARTENS D., BAESENS B., Social network analysis for customer churn

prediction, Applied Soft Computing, forthcoming, 2013. SCI 2012 Impact Factor:

2.140

[7] VANDEN BROUCKE S., DE WEERDT J., VANTHIENEN J., BAESENS B., Determining Process

Model Precision and Generalization with Weighted Artificial Negative Events, IEEE

Transactions on Knowledge and Data Engineering, forthcoming, 2013. SCI 2012

Impact Factor: 1.892

[8] LOUIS P., BAESENS B., Do for-profit microfinance institutions achieve better financial

efficiency and social impact?, Journal of Development Effectiveness, forthcoming,

2013. SCI 2012 Impact factor: 0.617

[9] CARON F., VANTHIENEN J., VANHAECHT K., VAN LIMBERGEN E., DE WEERDT J.,

BAESENS B., A Process Mining Based Investigation of Adverse Events in Care

Processes, Health Information Management Journal, forthcoming, 2013. SCI 2012

Impact factor: 0.704

[10] VERBRAKEN T., GOETHALS F, VERBEKE W., BAESENS B., Predicting Online Channel

Acceptance Using Social Network Data, Decision Support Systems, forthcoming, 2013.

SCI 2012 Impact factor: 2.201

1 Authors are always listed in order of contribution.


[11] LOUIS P., VAN LAERE E., BAESENS B., Understanding and predicting bank rating

transitions using optimal survival analysis models, Economics Letters, forthcoming,

2013, SCI 2012 Impact factor: 0.509

[12] LOUIS P., SERET A., BAESENS B., Financial Efficiency and Social Impact of

Microfinance Institutions using Self-Organizing Maps, World Development,

forthcoming, 2013. SCI 2012 Impact factor: 1.527

[13] CARON F., VANTHIENEN J., BAESENS B., A Comprehensive Investigation of the

Applicability of Process Mining Techniques for Enterprise Risk Management,

Computers in Industry, forthcoming, 2013. SCI 2012 Impact factor: 1.709

[14] BERTELOOT K., VERBEKE W., CASTERMANS G., VAN GESTEL T., MARTENS D., BAESENS

B., A novel credit rating migration modeling approach using macroeconomic

indicators, Journal of Forecasting, forthcoming, 2013. SCI 2012 Impact Factor:

0.769

[15] CARON F., VANTHIENEN J., BAESENS B., Comprehensive Rule-Based Compliance

Checking and Risk Management with Process Mining, Decision Support Systems,

forthcoming, 2013. SCI 2012 Impact factor: 2.201

[16] DE WEERDT J., VANDEN BROUCKE S., VANTHIENEN J., BAESENS B., Active Trace

Clustering for Improved Process Discovery, IEEE Transactions on Knowledge and

Data Engineering, forthcoming, 2013. SCI 2012 Impact Factor: 1.892

[17] MOGES H.T., DEJAEGER K., LEMAHIEU W., BAESENS B., A multidimensional Analysis of

Data Quality for Credit Risk Management: New Insights and Challenges, Information

and Management, forthcoming 2013. SCI 2012 Impact Factor: 1.663

[18] DE WEERDT J., SCHUPP A., VANDERLOOCK A., BAESENS B., Process Mining for the

multi-faceted analysis of business processes - A case study in a financial services

organization, Computers in Industry, Volume 64, Issue 1, pp. 57-67, 2013. SCI 2012


[19] MOGES H.T., DEJAEGER K., LEMAHIEU W., BAESENS B., A Total Data Quality

Management for Credit Risk: New insights and challenges, International Journal of

Information Quality, Volume 3, Number 1, pp. 1-27, 2012.

[20] MEHTA V., RYCYNA K., BAESENS B., BARKAN G.A., PANER G. P., FLANIGAN R. C.,

WOJCIK E. M., VENKATARAMAN G., Predictors of Gleason Score (GS) upgrading on

Subsequent Prostatectomy: A Single Institution Study in a Cohort of Patients with GS 6,

International Journal of Clinical and Experimental Pathology, Volume 5, Number 6,

pp. 496-502, 2012. SCI Impact Factor 2012: 2.242

[21] DE WEERDT J., DE BACKER M., VANTHIENEN J., BAESENS B., A multi-dimensional

quality assessment of state-of-the-art process discovery algorithms using real-life event

logs, Information Systems, Volume 37, Issue 7, pp. 654-676, 2012. SCI 2012 Impact

factor: 1.768

[22] VERBRAKEN T., VERBEKE W. BAESENS B., A Novel Profit Maximizing Metric for

Measuring Classification Performance of Customer Churn Prediction Models, IEEE


Transactions on Knowledge and Data Engineering, forthcoming, 2013. SCI 2012


[23] DEJAEGER K., VERBRAKEN T., BAESENS B., Towards Comprehensible Software Fault

Prediction Models Using Bayesian Network Classifiers, IEEE Transactions on Software

Engineering, Volume 39, Number 2, pp. 237-277, 2013. SCI 2012 Impact Factor:

2.588

[24] SERET A., VERBRAKEN T., VERSAILLES S., BAESENS B., A New SOM-Based Method for

Profile Generation: Theory and an Application in Direct Marketing, European Journal

of Operational Research, Volume 220, Issue 1, pp. 199-209, 2012. SCI 2012 Impact

Factor: 2.038

[25] VERBRAKEN T., VERBEKE W., BAESENS B., Profit Optimizing Customer Churn

Prediction with Bayesian Network Classifiers, Intelligent Data Analysis, forthcoming,

2013. SCI 2012 Impact Factor: 0.472

[26] BAESENS B., MARTENS D., SETIONO R., ZURADA J., White Box Nonlinear Prediction

Models, editorial special issue, IEEE Transactions on Neural Networks, Volume 22,

Number 12, pp. 2406-2408, 2011. SCI 2012 Impact Factor: 3.766

[27] DEJAEGER K., GOETHALS F., GIANGRECO A., MOLA L., BAESENS B., Gaining insight into

student satisfaction using comprehensible data mining techniques, European Journal of

Operational Research, Volume 218, Issue 2, pp. 548-562, 2012. SCI 2012 Impact

Factor: 2.038

[28] TSUJITANI M., BAESENS B., Survival Analysis for Personal Loan Data using Generalized

Additive Models, Behaviormetrika, Volume 39, Number 1, pp. 1-15, 2012.

[29] VERBEKE W., DEJAEGER K, MARTENS D., HUR J., BAESENS B., New insights into churn

prediction in the telecommunication sector: a profit driven data mining approach,

European Journal of Operational Research, Volume 218, Issue 1, pp. 211-229, 2012.

SCI 2012 Impact Factor: 2.038

[30] SETIONO R., BAESENS B. MUES C., Rule Extraction from Minimal Neural Network for

Credit Card Screening, International Journal of Neural Systems, Volume 21, Number 4,

pp. 265-276, 2011. SCI 2012 Impact Factor: 5.054

[31] LOTERMAN G., BROWN I., MARTENS D., MUES C., BAESENS B., Benchmarking

Regression Algorithms for Loss Given Default Modeling, International Journal of

Forecasting, Volume 28, Number 1, pp. 161-170, 2012. SCI 2012 Impact Factor:

1.424

[32] DEJAEGER K., VERBEKE W., MARTENS D., BAESENS B., Data Mining Techniques for

Software Effort Estimation: a Comparative Study, IEEE Transactions on Software

Engineering, Volume 38, Number 2, pp. 375-397, 2012. SCI 2012 Impact Factor:

2.588

[33] VAN GOOL J., VERBEKE W., SERCU, P., BAESENS B., Credit Scoring for Microfinance - is

it worth it?, International Journal of Finance and Economics, Volume 17, Issue 2, pp.

103-123, 2012. SCI 2012 Impact Factor: 0.784


[34] MARTENS D., VANHOUTTE C., DE WINNE S., BAESENS B. SELS L., MUES C., Identifying

Financially Successful Start-Up Profiles with Data Mining, Expert Systems with

Applications, Volume 38, pp. 5794–5800, 2011. SCI 2012 Impact Factor: 1.854

[35] HUYSMANS J., DEJAEGER K., MUES C., VANTHIENEN J., BAESENS B., An Empirical

Evaluation of the Comprehensibility of Decision Table, Tree and Rule Based Predictive

Models, Decision Support Systems, Volume 51, Issue 1, pp. 141-154, 2011. SCI 2012


[36] MARTENS D., FAWCETT T., BAESENS B., Editorial Survey: Swarm Intelligence for Data

Mining, Machine Learning, Volume 82, Number 1, pp. 1-42, 2010. SCI 2012 Impact

Factor: 1.467

[37] MARTENS D., VANTHIENEN J., VERBEKE W., BAESENS B., Performance of classification

models from a user perspective, Decision Support Systems, Special Issue on Recent

Advances in Data, Text, and Media Mining & Information Issues in Supply Chain and

in Service System Design, Volume 51, Issue 4, pp. 782 - 793, 2011. SCI 2012 Impact

factor: 2.201

[38] VERBEKE W., MARTENS D., MUES C., BAESENS B., Building comprehensible customer

churn prediction models with advanced rule induction techniques, Expert Systems with

Applications, Volume 38, pp. 2354-2364, 2011. SCI 2012 Impact Factor: 1.854

[39] VAN GESTEL T., MARTENS D., BAESENS B., From Linear to Non-linear Kernel Based

Classifiers for Bankruptcy Prediction, Neurocomputing, Volume 73, Number 16-18, pp.


[40] LIMA E., MUES C., BAESENS B., Monitoring and Backtesting Churn Models, Expert

Systems with Applications, Volume 38, Number 1, pp. 975-982, 2010. SCI 2012


[41] GOEDERTIER S., DE WEERDT J., MARTENS D., VANTHIENEN J., BAESENS B., Process

Discovery in Event Logs: An Application in the Telecom Industry, Applied Soft

Computing, Volume 11, Number 2, pp. 1697-1710, 2011. SCI 2012 Impact Factor:

2.140

[42] VUYLSTEKE A., WEN Z., POELMANS J., BAESENS B., Consumers' Search for Information

on the Internet: How and Why China Differs from Western Europe, Journal of

Interactive Marketing, Volume 24, Number 4, pp. 309-331, 2010. SCI 2012 Impact

Factor: 2.140

[43] VAN LAERE E., BAESENS B., The development of a simple and intuitive rating system

under Solvency II, Insurance: Mathematics and Economics, Volume 46, Issue 3, pp.


[44] CASTERMANS G., MARTENS D., VAN GESTEL T., HAMERS B., BAESENS B., An Overview

and Framework for PD Backtesting and Benchmarking, Journal of the Operational

Research Society, Special issue on Consumer Credit Risk Modeling, Volume 61, pp.



[45] MARTENS D., VAN GESTEL T., DE BACKER M., HAESEN R., VANTHIENEN J., BAESENS B.,

Credit Rating Prediction Using Ant Colony Optimization, Journal of the Operational

Research Society, Volume 61, pp. 561-573, 2010. SCI 2012 Impact Factor: 0.989

[46] BAESENS B., Data Mining: new trends, applications and challenges, Review of Business

and Economics, Number 1, pp. 46-61, 2009.

[47] LIMA E., MUES C., BAESENS B., Domain knowledge integration in data mining using

decision tables: case studies in churn prediction, Journal of the Operational Research

Society, Volume 60, pp. 1096-1106, 2009. SCI 2012 Impact Factor: 0.989

[48] GOEDERTIER S., MARTENS D., VANTHIENEN J., BAESENS B., Robust Process Discovery

with Artificial Negative Events, Journal of Machine Learning Research, Volume 10,


[49] VENKATARAMAN G., RYCYNA, K., RABANSER A., HEINZE G., BAESENS B.,

ANANTHANARAYANAN V., PANER G.P., BARKAN G.A., FLANIGAN R.C., WOJCIK E.V.,

Morphometric Signature differences exist Within Nuclei of Gleason Pattern 4 Areas In

Gleason 7 Prostate Cancer With Differing Primary Grades on Needle Biopsy, Journal of

Urology, Volume 181, Number 1, pp. 88-94, 2009. SCI 2012 Impact Factor: 3.696

[50] BAESENS B., MUES C., MARTENS D., VANTHIENEN J., 50 years of Data Mining and OR:

upcoming trends and challenges, Journal of the Operational Research Society, Volume

60, pp. 16-23, 2009. SCI 2012 Impact Factor: 0.989

[51] GLADY N., CROUX C., BAESENS B., Modeling Churn Using Customer Lifetime Value,

European Journal of Operational Research, Volume 197, Number 1, pp. 402-411,


[52] CUMPS B., MARTENS D., DE BACKER M., VIAENE S., DEDENE G., HAESEN R., SNOECK

M., BAESENS B., Inferring rules for business/ICT alignment using Ants, Information and

Management, Volume 46, Number 2, pp. 116-124, 2009. SCI 2012 Impact Factor:

1.663

[53] MARTENS D., BAESENS B., VAN GESTEL T., Decompositional Rule Extraction from

Support Vector Machines by Active Learning, IEEE Transactions on Knowledge and

Data Engineering, Volume 21, Number 1, pp. 178-191, 2009. SCI 2012 Impact

Factor: 1.892

[54] GLADY N., CROUX C., BAESENS B., A Modified Pareto/NBD Approach for Predicting

Customer Lifetime Value, Expert Systems With Applications, Volume 36, Number 2,


[55] SETIONO R. BAESENS B., MUES C., A note on knowledge discovery using neural

networks and its application to credit card screening, European Journal of Operational

Research, 2008, Volume 192 (1), pp.326-332, 2009. SCI 2012 Impact Factor: 2.038

[56] LESSMANN S., BAESENS B., MUES C., PIETSCH S., Benchmarking classification models

for software defect prediction: A proposed framework and novel findings, IEEE

Transactions on Software Engineering, Volume 34, Number 4, pp. 485-496, 2008. SCI

2012 Impact Factor: 2.588


[57] VAN LAERE E., BAESENS B., THIBEAULT A., Bank capital: a myth resolved, Tijdschrift

voor Bank en Financiewezen, Volume 1, 2008.

[58] MARTENS D., BRUYNSEELS L., BAESENS B., WILLEKENS M., VANTHIENEN J., Predicting

Going Concern Opinion with Data Mining, Decision Support Systems, Volume 45, pp.

765–777, 2008. SCI 2012 Impact factor: 2.201

[59] VANDECRUYS O., MARTENS D., BAESENS B., MUES C., DE BACKER M., HAESEN R.,

Mining Software Repositories for Comprehensible Software Fault Prediction Models,

Journal of Systems and Software, Volume 81, pp. 823-839, 2008. SCI 2012 Impact

Factor: 1.135

[60] HUYSMANS J., SETIONO R., BAESENS B., VANTHIENEN J., Minerva: sequential covering

for rule extraction, IEEE Transactions on Systems, Man and Cybernetics, Part B,

Volume 38, Number 2, pp. 299-309, 2008. SCI 2012 Impact Factor: 3.236

[61] SETIONO R., BAESENS B., MUES C. Recursive Neural Network Rule Extraction for Data

with Mixed Attributes, IEEE Transactions on Neural Networks, Volume 19, Number 2,


[62] VAN GESTEL T., MARTENS D., BAESENS B., FEREMANS D., HUYSMANS J., VANTHIENEN

J., Forecasting and Analyzing Insurance Companies’Ratings, International Journal of

Forecasting, Volume 23, Number 3, pp. 513-529, 2007. SCI 2012 Impact Factor:

1.424

[63] HUYSMANS J., BAESENS B., VANTHIENEN J., A New Approach for Measuring Rule Set

Consistency, Data and Knowledge Engineering, Volume 63, Number 1, pp. 167-182,


[64] MARTENS D., DE BACKER M., HAESEN R., VANTHIENEN J., SNOECK M., BAESENS B.,

Classification with Ant Colony Optimization, IEEE Transactions on Evolutionary

Computation, Volume 11, Number 5, pp. 651-665, 2007. SCI 2012 Impact Factor:

4.810 This paper was most frequently accessed during October 2007.

[65] MARTENS D., BAESENS B., VAN GESTEL T., VANTHIENEN J., Comprehensible Credit

Scoring Models Using Rule Extraction From Support Vector Machines, European

Journal of Operational Research, Volume 183, pp. 1466-1476, 2007. SCI 2012


[66] HOFFMANN F., BAESENS B., MUES C., VAN GESTEL T., VANTHIENEN J., Inferring

descriptive and approximate fuzzy rules for credit scoring using evolutionary

algorithms, European Journal of Operational Research, Volume 177, Number 1, pp.


[67] VAN GESTEL T., BAESENS B., VAN DIJCKE P., SUYKENS J., GARCIA J. AND

ALDERWEIRELD T., Linear and nonlinear credit scoring by combining logistic

regression and support vector machines, Journal of Credit Risk, Volume 1, Number

4, 2005.

[68] VAN GESTEL T., BAESENS B., VAN DIJCKE P., GARCIA J., SUYKENS J.A.K., VANTHIENEN

J., A process model to develop an internal rating system: sovereign credit ratings,


Decision Support Systems, Volume 42, Number 2, pp. 1131-1151, 2006. SCI 2012


[69] HUYSMANS J., BAESENS B., VAN GESTEL T., VANTHIENEN J., Failure prediction with Self

Organizing Maps, Expert Systems With Applications, Special Issue on Intelligent

Information Systems for Financial Engineering, Volume 30, Number 3, pp. 479-487,

April 2006. SCI 2012 Impact Factor: 1.854

[70] VAN GESTEL T., ESPINOZA M., BAESENS B., SUYKENS J.A.K., BRASSEUR C., DE MOOR

B., A Bayesian Nonlinear Support Vector Machine Error Correction Model, Journal of

Forecasting, Volume 25, pp. 77-100, 2006. SCI 2012 Impact Factor: 0.769

[71] SOMOL P., BAESENS B., PUDIL P., VANTHIENEN J., Filter-versus Wrapper-based Feature

Selection for Credit Scoring, International Journal of Intelligent Systems, Volume 20,

Number 10, pp. 985-999, 2005. SCI 2012 Impact Factor: 1.416

[72] BAESENS B., VAN GESTEL T., MUES C., VANTHIENEN J., Intelligent Information Systems

for Financial Engineering, Expert Systems With Applications, Special Issue on

Intelligent Information Systems for Financial Engineering, Volume 30, Number 3, pp.

413-414, April 2006. SCI 2012 Impact Factor: 1.854

[73] VAN GESTEL T., BAESENS B., SUYKENS J.A.K., VAN DEN POEL D., BAESTAENS D.-E.,

WILLEKENS M., Bayesian Kernel Based Classification for Financial Distress Detection,



[74] BAESENS B., VAN GESTEL T., STEPANOVA M., VAN DEN POEL D., VANTHIENEN J.,

Neural Network Survival Analysis for Personal Loan Data, Journal of the Operational

Research Society, Special Issue on Credit Scoring, Volume 59, Number 9, pp. 1089-

1098, 2005. . SCI 2012 Impact Factor: 0.989

[75] EGMONT-PETERSEN M., FEELDERS A., BAESENS B., Confidence Intervals for

Probabilistic Network Classifiers, Computational Statistics and Data Analysis, Volume

49, Issue 4, pp. 998-1019, 2005. SCI 2012 Impact Factor: 1.304

[76] MUES C., BAESENS B., FILES C.M., VANTHIENEN J., Decision Diagrams in Machine

Learning: an Empirical Study on Real-Life Credit-Risk Data, Expert Systems with

Applications, Volume 27, Issue 2, pp. 257-264, September 2004. SCI 2012 Impact

Factor: 1.854

[77] BAESENS B., SETIONO R., MUES C., VANTHIENEN J., Using Neural Network Rule

Extraction and Decision Tables for Credit-Risk Evaluation, Management Science,

Volume 49, Number 3, pp. 312-329, March 2003. SCI 2012 Impact Factor: 1.859

[78] BAESENS B., VAN GESTEL T., VIAENE S., STEPANOVA M., SUYKENS J., VANTHIENEN J.,

Benchmarking State of the Art Classification Algorithms for Credit Scoring, Journal of

the Operational Research Society, Volume 54, Number 6, pp. 627-635, 2003. SCI


[79] BAESENS B., VERSTRAETEN G., VAN DEN POEL D., EGMONT-PETERSEN M., VAN

KENHOVE P., VANTHIENEN J., Bayesian Network Classifiers for Identifying the Slope of

the Customer Lifecycle of Long-Life Customers, European Journal of Operational


Research, Volume 156, Number 2, pp. 508-523, 2004. SCI 2012 Impact Factor:

2.038

[80] VAN GESTEL T., BAESENS B., GARCIA J., VAN DIJCKE P., A Support Vector Machine

Approach to Credit Scoring, Bank en Financiewezen, Volume 2, pp. 73-82, March

2003.

[81] VAN GESTEL T., SUYKENS J., BAESENS B., VIAENE S., VANTHIENEN J., DEDENE G., DE

MOOR B., VANDEWALLE J., Benchmarking Least Squares Support Vector Machine

Classifiers, Machine Learning, Volume 54, Issue 1, pp. 5-32, January 2004. SCI 2014


[82] HOFFMANN F., BAESENS B., MARTENS J., PUT F., VANTHIENEN J., Comparing a Genetic

Fuzzy and a Neurofuzzy Classifier for Credit Scoring, International Journal of

Intelligent Systems, Volume 17, Issue 11, pp. 1067-1083, 2002. SCI 2012 Impact

Factor: 1.416

[83] VIAENE S., DERRIG R., BAESENS B., DEDENE G., A Comparison of State-of-the-Art

Classification Techniques for Expert Automobile Insurance Fraud Detection, Journal of

Risk and Insurance, Special issue on Fraud Detection, Volume 69, Issue 3, pp. 433-443,


[84] BAESENS B., VIAENE S., VAN DEN POEL D., VANTHIENEN J., DEDENE G., Bayesian

Neural Network Learning for Repeat Purchase Modelling in Direct Marketing,



[85] VIAENE S., BAESENS B., VAN DEN POEL D., DEDENE G., VANTHIENEN J., Wrapped Input

Selection using Multilayer Perceptrons for Repeat-Purchase Modeling in Direct

Marketing, International Journal of Intelligent Systems in Accounting, Finance and

Management, Volume 10, Number 2, pp. 115-126, 2001.

[86] VIAENE S., BAESENS B., VAN GESTEL T., SUYKENS J.A.K., VAN DEN POEL D.,

VANTHIENEN J., DE MOOR B., DEDENE G., Knowledge Discovery in a Direct Marketing

Case using Least Squares Support Vector Machines, International Journal of Intelligent

Systems, Volume 16, Number 9, pp. 1023-1036, 2001. SCI 2012 Impact Factor: 1.416

Books

[1] VAN GESTEL T., BAESENS B., Credit Risk Management: Model Risk Control, Oxford

University Press, 2016, forthcoming.

[2] VAN GESTEL T., BAESENS B., Credit Risk Management: Quantitative Modeling, Oxford

University Press, 2014, forthcoming.

[3] BAESENS B., Analytics in a Big Data World, Wiley, forthcoming, 2014.

[4] VAN GESTEL T., BAESENS B., Credit Risk Management: Basic concepts: financial risk

components, rating analysis, models, economic and regulatory capital, Oxford

University Press, ISBN 978-0-19-954511-7, 2009.

[5] BAESENS B., Developing Intelligent Systems for Credit Scoring Using Machine

Learning Techniques, Phd Thesis, KU Leuven, 2003.


Magazines

[1] VANDEN BROUCKE S., BAESENS B., LISMONT J., VANTHIENEN J., Sluit de lus: Moderne

technieken in Business Process Analytics, Informatie, Jan/Feb 2014.

[2] BAESENS B., VANDEN BROUCKE S., DEJAEGER K., EEROLA T., GOEDHUYS L., RIIS M.,

WEHKAMP R., Cloudcomputing in analytics: de hype ontraadseld, Informatie, maart, pp.

10-17, 2013.

[3] DEJAEGER K., VANDEN BROUCKE S., EEROLA T., WEHKAMP R., GOEDHUYS L., RIIS M.,

BAESENS B., Beyond the Hype: Cloud computing in Analytics, Cutter Consortium,

Executive update, Vol. 12, No. 16, 2012.

[4] DE WEERDT J., SCHUPP A., VANDERLOOCK A., BAESENS B., Datagedreven analyse van

bedrijfsprocessen op basis van process mining, Informatie, juli/augustus 2011.

[5] DEJAEGER K., VERBEKE W., MARTENS D. BAESENS B., Het voorspellen van software-

ontwikkelkosten, Informatie, november 2010.

[6] VAN GESTEL T., DEWYSPELAERE T., DEBLIQUY O., BAESENS B., Modelling Credit

Portfolios under Stress, Bank- en Financiewezen, Volume 7, pp. 416-422, 2010.

[7] DEJAEGER K., RUELENS J., VAN GESTEL T., JACOBS J., BAESENS B., POELMANS JONAS,

HAMERS B., Evaluatie en verbetering van de datakwaliteit, Informatie, Volume 51,

Number 9, pp. 8-15, 2009.

[8] VUYLSTEKE A., POELMANS J., BAESENS B., Online zoekgedrag van consumenten: China

vs West-Europa, Business In-Zicht, December 2009.

[9] BAESENS B., DE BACKER M., MARTENS D., Business intelligence + process management

= business process intelligence, Informatie, 2009.

[10] VERBEKE W., BAESENS B., Van credit crunch naar ICT crash, of niet?, Data News,

Number 1, 2009.

[11] DE BACKER M., BAESENS B., BPMN 2.0: meer dan een naamsverandering?, Informatie,

2009.

[12] BAESENS B., DE BACKER M., Business Intelligence: new trends, Informatie, 2009.

[13] BAESENS B., MARTENS D., ICT uitdagingen in het Basel II tijdperk, Informatie, Maart,

2008.

[14] BAESENS B., It’s the data, you stupid!, Data News, forthcoming 2007.

[15] MARTENS D., DE BACKER M., HAESEN R., BAESENS B., Artificiële mieren en hun

zoektocht naar kennis: Datamining met AntMiner+, Informatie, Mei, 2006.

[16] HUYSMANS J., BAESENS B., MARTENS D., DENYS K., VANTHIENEN J., New Trends in

Data Mining, Tijdschrift voor Economie en Management, Volume L., September 2005.

[17] HAESEN R., MARTENS D., DE BACKER M., BAESENS B., AntMiner+: Een systeem van

kennis-ontginnende mieren, Business IN-zicht, Nummer 20, November 2005.


[18] VAN GESTEL T., BAESENS B., VANTHIENEN J., De impact van Basel II op ICT: een

globaal overzicht, Informatie, 2004.

[19] BAESENS B., Het ontwikkelen van intelligente systemen voor krediettoekenning met

behulp van machine learning technieken, Beleidsinformatica Tijdschrift, Volume 29,

Nummer 2, 2003.

[20] HUYSMANS J., BAESENS, B., VANTHIENEN J., Web Usage Mining: een praktijkstudie,

Beleidsinformatica Tijdschrift, Volume 29, Nummer 2, 2003.

[21] BAESENS B., MUES C., VANTHIENEN J., Knowledge Discovery in Data: naar performante

én begrijpelijke modellen van bedrijfsintelligentie, Business IN-zicht, Nummer 12,

Maart 2003.

[22] BAESENS B., MUES C., VANTHIENEN J., Knowledge Discovery in Data: van academische

denkoefening naar bedrijfsrelevante praktijk, Informatie, pp. 30-35, Februari, 2003.

[23] SOUVEREIN M., BAESENS B., VIAENE S., VANDERBIST D., VANTHIENEN J., Een overzicht

van web usage mining en de implicaties voor e-commerce, Beleidsinformatica

Tijdschrift, Volume 27, Nummer 2, 2001.

[24] BAESENS B., ORDBMS'en: de object-relationele verzoening, Beleidsinformatica

Tijdschrift, Volume 24, Nummer 3, 1998.

Contributions to Books

[1] VERBRAKEN T., VAN VLASSELAER V., VERBEKE W., MARTENS D., BAESENS B.,

Advanced rule base learning: active learning, rule extraction, and incorporating domain

knowledge, Advanced Database Marketing, Coussement K., De Bock K., Neslin S.

(eds.), forthcoming, 2012.

[2] SETIONO R., BAESENS B., MARTENS D., Rule extraction from neural networks and

support vector machines for credit scoring, Data Mining: Foundations and Intelligent

Paradigms, D.E. Holmes, L.C. Jain (Eds.), ISRL 25, Springer, 2011.

[3] MARTENS D., BAESENS B., Building Acceptable Classification Models, Annals of

Information Systems, Special issue on Data Mining, Stahlbock, R; Crone, S.F.;

Lessmann, S. (Eds.), Springer, 2009.

[4] MARTENS D., HUYSMANS J., SETIONO R., VANTHIENEN J., BAESENS B., 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, Volume 80, Springer, pp. 33-63, 2006.

[5] MUES C., BAESENS B., HUYSMANS J., VANTHIENEN J., Comprehensible Credit-Scoring

Knowledge Visualization using Decision Tables and Diagrams, Enterprise Information

Systems VI, I. Seruca, I. Cordeiro, S. Hammoudi, J. Filipe (Eds.), Springer, pp. 109-115,

2006.

[6] MARTENS D., DE BACKER M., HAESEN R., BAESENS B., HOLVOET T., Ants constructing

rule-based classifiers, Swarm Intelligence in Data Mining/Stigmergic Optimization,

Ajith Abraham, Crina Grosan, Vitorino Ramos (Eds.), Springer Engineering Book

Series, Springer, 2005.


[7] BAESENS B., MUES C., SETIONO R., DE BACKER M., VANTHIENEN J., Building Intelligent

Credit Scoring Systems using Decision Tables, Enterprise Information Systems V,

Olivier Camp, Joaquim B.L. Filipe, Slimane Hammoudi, Mario G. Piattini (Eds.),

Kluwer, 2003.

[8] VIAENE S., BAESENS B., DEDENE G., VANTHIENEN J., VAN DEN POEL D., Proof Running

Two State-of-the-Art Pattern Recognition Techniques in the Field of Direct Marketing,

Enterprise Information Systems IV, Piattini M., Filipe J., Braz J. (Eds), Kluwer, 2002.

[9] HOFFMANN F., BAESENS B., MARTENS J., PUT F., VANTHIENEN J., Comparing a Genetic

Fuzzy and a Neurofuzzy Classifier for Credit Scoring, Proceedings of the Fifth

International FLINS Conference on Computational Intelligent Systems for Applied

Research (FLINS’2002), Ruan D., D’hondt P., Kerre E.E. (Eds), ISBN 981-238-066-3,

World Scientific, pp. 355-362, 2002.

[10] BAESENS B., SETIONO R., MUES C., VIAENE S., VANTHIENEN J., Building Credit-Risk

Evaluation Expert Systems using Neural Network Rule Extraction and Decision Tables,

New Directions in Software Engineering, Liber Amicorum M. Verhelst, Vandenbulcke

J. and Snoeck M. (Eds.), 160 pp., Leuven University Press, 2001.

Conference Publications

[1] VANDEN BROUCKE S., VANTHIENEN J., BAESENS B., Declarative Process Discovery with

Evolutionary Computing, Proceedings of the 2014 IEEE Congress on Evolutionary

Computation, Bejing, China, July 6-11, 2014.

[2] BACKIEL A., BAESENS B., CLAESKENS G., Mining Telecommunication Networks to

Enhance Customer Lifetime Predictions, Proceedings of the 13th International

Conference on Artificial Intelligence and Soft Computing (ICAISC), Lecture Notes in

Artificial Intelligence, Springer, Zakopane, Poland, June 1-5, 2014.

[3] LI L., GOETHALS F., BAESENS B., Predicting e-commerce adoption using data about

product search and supplier search behavior, Proceedings of The 13th International

Conference on Electronic Business (ICEB2013), Nanyang university, Singapore, 2013.

[4] LI L.,GOETHALS F. & BAESENS B., Predicting e-commerce adoption using data about

product search and supplier search behavior, Proceedings of the 13th International

Conference on Electronic Business (ICEB2013), Nanyang university, Singapore, 2013.

[5] LI L., GOETHALS F., BAESENS B., GIANGRECO A., Using social network data to predict

technology acceptance, Proceedings of the International Conference on Information

Systems (ICIS2013), Milano, Italy, 2013.

[6] VANDEN BROUCKE S., DELVAUX, C., FREITAS, J., ROGOVA, T., VANTHIENEN, J.,

BAESENS, B., Uncovering the Relationship between Event Log Characteristics and

Process Discovery Techniques, Proceedings of the Workshop on Business Process

Intelligence (BPI2013), Beijing (China), 26-30 August 2013.

[7] VANDEN BROUCKE, S., CARON, F., VANTHIENEN, J., BAESENS, B., Validating and

Enhancing Declarative Business Process Models Based on Allowed and Non-Occurring

Past Behavior, Proceedings of the Workshop on Decision Mining & Modeling for

Business Processes (DeMiMoP’13), Beijing (China), 26-30 August 2013.


[8] SERET, A., VANDEN BROUCKE, S., BAESENS, B., VANTHIENEN, J., An Exploratory

Approach for Understanding Customer Behavior Processes Bases on Clustering and

Sequence Mining, Proceedings of the Workshop on Decision Mining & Modeling for

Business Processes (DeMiMoP’13), Beijing (China), 26-30 August 2013.

[9] CARON F., VANTHIENEN J., BAESENS B., Healthcare Analytics: Examining the

Diagnosis-Treatment Cycle, Proceedings of the CENTERIS 2013 - Conference on

ENTERprise Information Systems / HCIST 2013 - International Conference on Health

and Social Care Information Systems and Technologies, 23-25 October, Lisbon,

Portugal.

[10] DIRICK L., CLAESKENS G., BAESENS B., A New Approach for Variable Selection in

Mixture Cure Models for Predicting Time of Default, Proceedings of the Credit Scoring

and Credit Control XIII Conference, Edinburgh, 28-30 August 2013.

[11] VANTIEGHEM J., VAN LAERE E., BAESENS B., The difference between Moody's and S&P

bank ratings: is discretion in the rating process causing a split?, Proceedings of the Fifth

International IFABS conference, Nottingham, 2013.

[12] VAN DEN BROUCKE S., DE WEERDT J., VANTHIENEN J., BAESENS B., A Comprehensive

Benchmarking Framework (CoBeFra) for Conformance Analysis between Procedural

Process Models and Event Logs in ProM, Proceedings of the 2013 IEEE Symposium

Series on Computational Intelligence, Singapore, April 15-19, 2013.

[13] VERBRAKEN, T., LESSMANN S., BAESENS, B., Toward Profit-Driven Churn Modeling

with Predictive Marketing Analytics, Cloud Computing and Analytics: Innovations in

E-Business Services, The Eleventh Workshop on E-Business (WEB2012), Orlando (US),

December 15, 2012.

[14] MOGES H. T., LEMAHIEU W., BAESENS B., The Use of Data Quality Information (DQI)

for Decision-Making: An Exploratory Study, Proceedings of the International

Conference on Business Management & Information Systems, Singapore, November 22-

24, 2012.

[15] DE WEERDT J., CARON F., VANTHIENEN J., BAESENS B., Getting a Grasp on Clinical

Pathway Data: An Approach Based on Process Mining, Proceedings of the Third

Workshop on Data Mining for Healthcare Management, Kuala Lumpur, Malaysia, May

29 -June 1, 2012.

[16] DE WEERDT J., VANDEN BROUCKE S., VANTHIENEN J., BAESENS B., Leveraging Process

Discovery with Trace Clustering and Text Mining for Intelligent Analysis of Incident

Management Processes, Proceedings of the 2012 IEEE Congress on Evolutionary

Computation, Brisbane, Australia, June 10-15, 2012.

[17] VANDEN BROUCKE S., DE WEERDT J., BAESENS B., DE WEERDT J., Improved Artificial

Negative Event Generation to Enhance Process Event Logs, Proceedings of the 24th

International Conference on Advanced Information Systems Engineering, (CAiSE'12),

Lecture Notes in Computer Science, Springer, Gdańsk, Poland, June 25 - 29, 2012.

[18] VERBRAKEN T., GOETHALS F., VERBEKE W., BAESENS B., Using Social Network

Classifiers for Predicting E-Commerce Adoption, Proceedings of The Tenth Workshop

on E-Business (WEB2011), Shanghai, China, December 4, 2011.


[19] LOUIS P., VAN LAERE E., BAESENS B., Predicting bank rating transitions using optimal

competing risks survival analysis models, Proceedings of the Credit Scoring and Credit

Control XII conference, Edinburgh (United Kingdom), August 24-26, 2011.

[20] LOUIS P., VAN LAERE E., BAESENS B., Motivating and predicting bank rating transitions

using optimal survival analysis models, Proceedings of the 24th Australasian Finance

& Banking Conference. Sydney (Australia), December 14-16, 2011.

[21] VAN LAERE E., BAESENS B., Analyzing Bank Ratings: Key Determinants and

Procyclicality, Proceedings of the 24th Annual Australasian Finance and Banking

Conference, Sydney, December 14th - 16th, 2011.

[22] MOGES H. T., DEJAEGER K., LEMAHIEU W., BAESENS B., Data Quality for Credit Risk

Management: New Insights and Challenges, Proceedings of the International

Conference on Information Quality (ICIQ 2011), University of South Australia,

Adelaide, Australia, November 18-20, 2011.

[23] VERBEKE W., VERBRAKEN T., MARTENS D., BAESENS B., Relational Learning for

Customer Churn Prediction: The Complementarity of Networked and Non-Networked

Classifiers, Proceedings of the Second conference on the Analysis of Mobile Phone

Datasets and Networks, Cambridge (US), October 10-11, 2011.

[24] DE WEERDT J., DE BACKER M., VANTHIENEN J., BAESENS B., A Robust F-measure for

Evaluating Discovered Process Models, Proceedings of the IEEE Symposium Series in

Computational Intelligence 2011 (SSCI 2011), Paris, France, April 2011, Poster

Presentation.

[25] DE WEERDT J., DE BACKER M., VANTHIENEN J., BAESENS B., A critical evaluation study

of model-log metrics in process discovery, Proceedings of the 6th International

Workshop on Business Process Intelligence (BPI’10), New York, U.S., 2010,

forthcoming.

[26] DEJAEGER K, HAMERS B., POELMANS J., BAESENS B., A Novel Approach to the

Evaluation and Improvement of Data Quality in the Financial Sector, Proceedings of the

International Conference on Information Quality (ICIQ 2010), Little Rock, AR, United

States, 2010.

[27] BAOJUN M., DEJAEGER K., VANTHIENEN J., BAESENS B., Software defect prediction

based on association rule classification, Proceedings of the International Conference on

Electronic-Business Intelligence (ICEBI 2010), Kunming, China, December 19-21,

2010.

[28] SETIONO R., DEJAEGER K., VERBEKE W., MARTENS D., BAESENS B., Software Effort

Prediction using Regression Rule Extraction from Neural Networks, Proceedings of

22th International Conference on Tools with Artificial Intelligence, October 27-29,

2010, Arras, France.

[29] VAN LAERE E., BAESENS B., The Development of a Simple and Intuitive Rating System

under Solvency II, Proceedings of the Midwest Finance Association 2010 Conference,

Las Vegas, NV, U.S.A., February 24-27, 2010.


[30] VERBEKE W., BAESENS B., MARTENS D., DE BACKER M., HAESEN R., Building

Accurate, Comprehensible, and Justifiable Customer Churn Prediction Models using

AntMiner+, Proceedings of the Joint Statistical Meeting, Washington D.C., U.S.A.,

August 2009.

[31] VERBEKE W., BAESENS B., MARTENS D., DE BACKER M., HAESEN R., Including Domain

Knowledge in Customer Churn Prediction Using AntMiner+, Proceedings of the Ninth

Industrial Conference on Data Mining - Workshop DMM 2009, Leipzig, Germany, pp.

10-21, July 2009.

[32] VUYLSTEKE A., WEN Z., BAESENS B., POELMANS J., Consumer online information

search: a cross-cultural study between China and Western Europe, Proceedings of the

Academic and Business Research Institute Conference, Orlando, US, pp. 1-14,

September 24-26, 2009.

[33] LOTERMAN G., BROWN I., MARTENS C., MUES C., BAESENS B., Benchmarking state-of-

the-art regression algorithms for loss given default modelling, Proceedings of the

Conference on Credit Scoring and Credit Control, Edinburgh, United Kingdom, August

2009.

[34] MARTENS D., VAN GESTEL T., VANDEN BRANDEN K., JACOBS J., BAESENS B., A

Practical Framework for Credit Risk Stress Testing, Proceedings of the Conference on

Credit Scoring and Credit Control, Edinburgh, United Kingdom, August 2009.

[35] VANHOUTTE C., MARTENS D., DE WINNE S., SELS L., BAESENS B., The initial resource-

performance relationship in new ventures: Towards a configurational approach,

Proceedings of the Seventh AGSE Conference, Queensland, Australia, February 2-5,

2010. McGraw Hill Australia Honourable Mention for Paper in Entrepreneurship

Finance, Profitability & Growth.

[36] VAN LAERE E., BAESENS B., Regulatory and economic capital: theory and practice,

evidence from the field, Proceedings of the International Risk Management Conference

2009, Financial instability. A new world framework?, Venice, June 22-24, 2009.

[37] WESSA P., BAESENS B., Explorative Data Mining of Constructivist Learning

Experiences and Activities with Multiple Dimensions, Proceedings of the International

Conference on Computer and Instructional Technologies, Dubai, United Arab Emirates,

2009.

[38] WESSA P., BAESENS B., Fraud Detection in Statistics Education based on the

Compendium Platform and Reproducible Computing, IEEE Proceedings of the World

Congress on Computer Science and Information Engineering, Los Angeles/Anaheim,

USA, 2009.

[39] VAN LAERE E., BAESENS B., The development of a simple and intuitive rating system

under Solvency II, Proceedings of the International Risk Management Conference

(IRMC 2008), Credit and Financial Risk Management: 40 years after the Altman Z-

score model, Florence, Italy, June, 2008.

[40] BAESENS B., SETIONO R., MUES C., Neural Network Rule Extraction and Decision

Tables for Software Fault Prediction, Proceedings of the Fourteenth International

Conference on Neural Information Processing (ICONIP 2007), Special session on

http://www.informatik.uni-trier.de/~ley/db/conf/incdm/incdm2009w.html#VerbekeBMBH09


"Innovation in Machine Learning and Data Mining”, Lecture Notes in Computer

Science, Springer, Kitakyushu, Japan, 2007. SCI 2005 Impact Factor: 0.402

[41] GOEDERTIER S., MARTENS D., BAESENS B., HAESEN R., VANTHIENEN J., Process Mining

as First-Order Classification Learning on Logs with Negative Events, Proceedings of

the third Workshop on Business Process Intelligence (BPI 07), Lecture Notes In

Computer Science, Springer, Brisbane, Australia, September 25-27, 2007. SCI 2005


[42] GLADY N., BAESENS B., CROUX C., A Modified Pareto/NBD Approach for Predicting

Customer Lifetime Value, Proceedings of the Statistics for Data Mining, Learning and

Knowledge Extraction (IASC 07) Conference, Aveiro, Portugal, August 30 September

1, 2007.

[43] GLADY N., BAESENS B., CROUX C., A Modified Pareto/NBD Approach for Predicting

Customer Lifetime Value, 39e Journées de Statistiques ( JDS 2007), Angers, 2007.

[44] SETIONO R., BAESENS B., MUES C., Risk Management and Regulatory Compliance: A

Data Mining Framework Based on Neural Network Rule Extraction, Proceedings of the

International Conference on Information Systems (ICIS 2006), Milwaukee, Wisconsin,

pp. 71-85, December 10-13, 2006. Best paper Design track

[45] HUYSMANS J., BAESENS B., VANTHIENEN J., ITER: an Algorithm for Predictive

Regression Rule Extraction, Proceedings of the Eighth International Conference on

Data Warehousing and Knowledge Discovery (DAWAK), Lecture Notes In Computer

Science 4081, Springer, pp. 270-279, Krakow, Poland, September 4-8, 2006. SCI 2005


[46] MARTENS D., DE BACKER M., HAESEN R., BAESENS B., MUES C., VANTHIENEN J., Ant-

Based Approach to the Knowledge Fusion Problem, Proceedings of the Fifth

International Workshop on Ant Colony Optimization and Swarm Intelligence (ANTS

2006), Lecture Notes In Computer Science, Springer, pp. 85-96, Brussels, Belgium,

September 4-7, 2006, forthcoming. SCI 2005 Impact Factor: 0.402

[47] HUYSMANS J., MARTENS D., BAESENS B., VANTHIENEN J., Country Corruption Analysis

with Self Organizing Maps and Support Vector Machines, Proceedings of the Tenth

Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006),

Workshop on Intelligence and Security Informatics (WISI), Lecture Notes in Computer

Science, volume 3917, pp. 103-114, Springer-Verlag, Singapore, April 9, 2006. SCI


[48] VAN GESTEL T., SUYKENS J.A.K., PELCKMANS K., BAESENS B., Credit Rating Systems

by Combining Linear Ordinal Logistic Regression and Fixed-Size Least Squares

Support Vector Machines, Workshop on Machine Learning in Finance, NIPS 2005

Conference, Whistler, British Columbia, Canada, December 9, 2005.

[49] DE BACKER M., HAESEN R., MARTENS D., BAESENS B., A Stigmergy Based Approach to

Data Mining, Proceedings of the Eighteenth Australian Joint Conference on Artificial

Intelligence (AI 2005), Lecture Notes in Computer Science, Springer-Verlag, pp. 975 –

978, Sydney, Australia, December 5-9, 2005. SCI 2005 Impact Factor: 0.402


[50] MARTENS D., BAESENS B., VAN GESTEL T., VANTHIENEN J., Adding Comprehensibility

to Support Vector Machine Models Using Rule Extraction Techniques, Proceedings of

the Ninth Credit Scoring and Credit Control Conference (CSCCIX’'2005), Edinburgh,

United Kingdom, September 2005.

[51] MEEUS N., HUYSMANS J., BAESENS B., VANTHIENEN J., VANDEBROEK M., .The use of

Knowledge Discovery Techniques for Behavioural Scoring, Proceedings of the Sixth

International Conference on Data Mining, Text Mining and their Business Applications,

May 25-27, Skiathos, Greece, 2005.

[52] HUYSMANS J., BAESENS B., VANTHIENEN J., A comprehensible SOM-based Scoring

System, Proceedings of the International Conference on Machine Learning and Data

Mining (MLDM´2005), Lecture Notes in Computer Science, Springer-Verlag, Leipzig,

Germany, July 9-11, pp. 80-89, 2005. SCI 2005 Impact Factor: 0.402

[53] MUES C., BAESENS B., VANTHIENEN J., From Knowledge Discovery to Implementation:

Developing Business Intelligence Systems using Decision Tables, Proceedings of the

Workshop on Knowledge Management and Business Intelligence, Lecture Notes in

Computer Science, Springer-Verlag, Kaiserslautern, Germany, April 10-13, pp. 483-

495, 2005. SCI 2005 Impact Factor: 0.402

[54] HUYSMANS J., BAESENS B., VANTHIENEN J., The influence of caching on web usage

mining, Proceedings of the Fifth International Conference on Data Mining, Text Mining

and their Business Applications, Malaga, Spain, pp.77-86, September 2004.

[55] HUYSMANS J., BAESENS B., MUES C., VANTHIENEN J., Web usage mining with time

constrained association rules, Proceedings of the Sixth International Conference on

Enterprise Information Systems (ICEIS 2004), Porto, Portugal, pp. 343-348, April 2004.

[56] VAN DE WALLE P., CALLEWAERT B., HUENAERTS C., MOLENAERS G., MEEUSEN C., NIJS

J., BAESENS B., DESLOOVERE K., A Study on Maturation of Oxygen Rate and Cost

During Walking and the Influence of Net Non-Dimensional Normalization using Sitting

and Standing Data, Proceedings of the Thirteenth Annual ESMAC meeting, Warsaw,

Poland, September 23-25, 2004.

[57] MUES C., BAESENS B., HUYSMANS J., VANTHIENEN J., Comprehensible Credit-Scoring

Knowledge Visualization Using Decision Tables And Diagrams, Proceedings of the

Sixth International Conference on Enterprise Information Systems (ICEIS 2004), Porto,

Portugal, pp. 226-232, April 2004.

[58] HUYSMANS J., BAESENS B., VANTHIENEN J., Web usage mining: a practical study,

Proceedings of the Twelfth Conference on Knowledge Acquisition and Management

(KAM 2004), Kule, Poland, May 2004.

[59] MUES C., BAESENS B., FILES C. M., VANTHIENEN J., Decision diagrams in machine

learning: an empirical study on real-life credit-risk data, Proceedings of the Third

International Conference on the Theory and Application of Diagrams (Diagrams 2004),

Lecture Notes in Computer Science, Springer-Verlag, Cambridge, United Kingdom,

March 22-24, 2004. SCI 2005 Impact Factor: 0.402


[60] BAESENS B.,VAN GESTEL T., STEPANOVA M., VANTHIENEN J., Neural Network Survival

Analysis for Personal Loan Data, Proceedings of the Eighth Conference on Credit

Scoring and Credit Control (CSCCVII'2003), Edinburgh, Scotland, September, 2003.

[61] EGMONT-PETERSEN M., BAESENS B., FEELDERS A., Using Bayesian Networks for

Estimating the Risk of Default in Credit Scoring, Proceedings of the International

Workshop on Computational Management Science, Economics, Finance and

Engineering, Limassol, Cyprus, March 2003.

[62] BAESENS B., MUES C., SETIONO R., DE BACKER M., VANTHIENEN J., Building Intelligent

Credit Scoring Systems using Decision Tables, Proceedings of the Fifth International

Conference on Enterprise Information Systems (ICEIS’2003), Angers, France, pp. 19-

25, April 2003. Best paper nomination

[63] VAN GESTEL T., BAESENS B., SUYKENS J., ESPINOZA M., BAESTAENS D.E., VANTHIENEN

J., DE MOOR B., Bankruptcy Prediction with Least Squares Support Vector Machine

Classifiers, Proceedings of the IEEE International Conference on Computational

Intelligence for Financial Engineering (CIFEr2003), Hong Kong, pp. 1-8, March 2003.

[64] BUCKINX W., BAESENS B., VAN DEN POEL D., VAN KENHOVE P., VANTHIENEN J., Using

Machine Learning Techniques to Predict Defection of Top Clients, Proceedings of the

Third International Conference on Data Mining Methods and Databases for

Engineering, Finance and Other Fields, Bologna, Italy, pp. 509-517, September 2002.

[65] BAESENS B., EGMONT-PETERSEN M., CASTELO R., VANTHIENEN J., Learning Bayesian

Network Classifiers for Credit Scoring using Markov Chain Monte Carlo Search,

Proceedings of the Sixteenth International Conference on Pattern Recognition

(ICPR'2002), IEEE Computer Society, Québec, Canada, pp. 49-52, August 2002.

[66] VERSTRAETEN G., BAESENS B.,VAN DEN POEL D., EGMONT-PETERSEN M., VAN

KENHOVE P., VANTHIENEN J., Targeting Long-Life Customers: Towards a Segmented

CRM Approach, Proceedings of the Thirty-First European Marketing Academy

Conference (EMAC’2002), Braga, Portugal, May 2002.

[67] VIAENE S., BAESENS B., DEDENE G., VANTHIENEN J., VAN DEN POEL D., Proof Running

Two State-of-the-Art Pattern Recognition Techniques in the Field of Direct Marketing,

Proceedings of the Fourth International Conference on Enterprise Information Systems

(ICEIS’2002), Ciudad Real, Spain, pp. 446-454, April 2002. Best paper nomination

[68] BAESENS B., SETIONO R., MUES C., VIAENE S., VANTHIENEN J., Building Credit-Risk

Evaluation Expert Systems using Neural Network Rule Extraction and Decision Tables,

Proceedings of the Twenty Second International Conference on Information Systems

(ICIS’2001), New Orleans, Louisiana, USA, December, 2001.

[69] BAESENS B., SETIONO R., DE LILLE V., VIAENE S., VANTHIENEN J., Neural Network Rule

Extraction for Credit Scoring, Proceedings of The Pacific Asian Conference on

Intelligent Systems (PAIS’2001), Seoul, Korea, pp. 128-132, November, 2001.

[70] VIAENE S., DERRIG R., BAESENS B., DEDENE G., A Comparison of State-of-the-Art

Classification Techniques for Expert Automobile Insurance Fraud Detection,

Proceedings of the Fifth International Congress on Insurance: Mathematics and

Economics (IME'2001), Pennsylvania, USA, July, 2001.


[71] VIAENE S., BAESENS B., VAN DEN POEL D., VANTHIENEN J., DEDENE G., The Bayesian

Evidence Framework for Database Marketing Modeling using both RFM and Non-RFM

Predictors, Proceedings of the Fifth World Multi-Conference on Systemics, Cybernetics

and Informatics (SCI'2001), Orlando, Florida, USA, pp.136-140, July, 2001. Best

paper nomination

[72] BAESENS B., VIAENE S., VANTHIENEN J., A Comparative Study of State of the Art

Classification Algorithms for Credit Scoring, Proceedings of the Seventh Conference on

Credit Scoring and Credit Control (CSCCVII'2001), Edinburgh, Scotland, September,

2001.

[73] BAESENS B., VIAENE S., VAN GESTEL T., SUYKENS J.A.K., DEDENE G., DE MOOR B.,

VANTHIENEN J., An Initial Approach to Wrapped Input Selection using Least Squares

Support Vector Machine Classifiers: Some Empirical Results, Proceedings of the

Twelfth Belgium-Netherlands Conference on Artificial Intelligence (BNAIC'00),

Kaatsheuvel, The Netherlands, pp. 69-76, November, 2000.

[74] BAESENS B., VIAENE S., VANTHIENEN J., DEDENE G., Wrapped Feature Selection by

means of Guided Neural Network Optimisation, Proceedings of the Fifteenth

International Conference on Pattern Recognition (ICPR'2000), IEEE Computer

Society, Barcelona, Spain, pp. 113-116, September, 2000.


VANTHIENEN J., DE MOOR B., DEDENE G., Knowledge Discovery using Least Squares

Support Vector Machine Classifiers: a Direct Marketing Case, Proceedings of the

Fourth European Conference on Principles and Practice of Knowledge Discovery in

Databases (PKDD'2000), D.A. Zighed, J. Komorowski and J. Zytkow (Eds.), Lecture

Notes in Artificial Intelligence 1910, Springer, Lyon, France, pp. 657-664, September,



VANTHIENEN J., An Empirical assessment of Kernel Type Performance for Least

Squares Support Vector Machine Classifiers, Proceedings of the Fourth International

Conference on Knowledge-Based Intelligent Engineering Systems & Allied

Technologies (KES'2000), University of Brighton, UK, pp. 313-316, September, 2000.

[77] VIAENE S., BAESENS B., VAN DEN POEL D., DEDENE G., VANTHIENEN J., Wrapped

Feature Selection for Binary Classification Bayesian Regularisation Neural Networks: a

Database Marketing Application, Proceedings of the Second International Conference

on DATA MINING 2000, Cambridge University, UK, pp. 353-362, July, 2000.

[78] BAESENS B., VIAENE S., VANTHIENEN J., Post-Processing of Association Rules,

Proceedings of the special workshop on post-processing, The Sixth ACM SIGKDD

International Conference on Knowledge Discovery and Data Mining (KDD'2000),

Boston, MA, USA, pp. 2-8, August, 2000.


Proceedings of the VIII Seminar on Knowledge Acquisition in Databases, Turawa,

Poland, pp.159-173, May, 2000.

[80] VIAENE S., BAESENS B., DEDENE G., VANTHIENEN J., VANDENBULCKE J., Sensitivity

Based Pruning of Input Variables by means of Weight Cascaded Retraining,


Proceedings of the Fourth International Conference and Exhibition on the Practical

Application of Knowledge Discovery and Data Mining (PADD'2000), Manchester, UK,

pp.141-159, April, 2000.

Book and Article Reviews

[1] BAESENS B., Efficient Construction of Regression Trees with Range and Region

Splitting, Morimoto Y., Ishii H., Morishita S., Machine Learning, Volume 45, pp. 235-

259, Computing Reviews, November 2002, ACM Press.

[2] BAESENS B., A fast algorithm for mining sequential patterns from large databases, Lu

L., Longxiang Z., An C., Ning C., Journal of Computer Science and Technology,

Volume 16, Number 4, pp. 359-370, Computing Reviews, April 2002, ACM Press.

[3] BAESENS B., Exploring data mining implementation, Hirji K., Communications of the

ACM, 44(7): 87-93, 2001, Computing Reviews, September 2001, ACM Press.

[4] BAESENS B., Interactive data warehousing, Singh Harry, Prentice Hall PTR, Upper

Saddle River, NJ, 1998, 481 pp., $49.99, ISBN 0-13-080371-5, Computing Reviews,

Volume 40, Number 8, August 1999, pp. 385-386, ACM Press.

[5] BAESENS B., 90 days to the data mart, Simon Alan, John Wiley & Sons, Inc., New

York, NY, 1998, 338 pp., $29.99, ISBN 0-471-25194-1, Computing Reviews, Volume

39, Number 10, October 1998, pp. 510-511, ACM Press.

Research reports2

[1] VANDEN BROUCKE S. K.L.M, MUÑOZ-GAMA, J., CARMONA, J., BAESENS B.,

VANTHIENEN J., Event-based Real-time Decomposed Conformance Analysis.

Polytechnic University of Catalonia, Department of Information Languages and

Systems, Technical Report LSI-13-12-R, 2013.

[2] TOBBACK E., MARTENS D., VAN GESTEL T., BAESENS B., Forecasting Loss Given

Default Models: Impact of Account Characteristics and The Macroeconomic State,

Working paper 2012/019, Universiteit Antwerpen, 2012.

[3] VAN LAERE E., BAESENS B., THIBEAULT A., Bank Capital: a myth resolved, Vlerick

Leuven Gent Working Paper series, WP 2007/35, 2007.

[4] GOEDERTIER S., MARTENS D., BAESENS B., HAESEN R., VANTHIENEN J., A New

Approach for Discovering Business Process Models From Event Logs, Research

Report, Department of Decision Sciences and Information Management, KBI 0716,

Katholieke Universiteit Leuven, 2007.

[5] HUYSMANS J., BAESENS B., VANTHIENEN J., Using rule extraction to improve the

comprehensibility of predictive models, Research Report 0612, Department of Decision

Sciences and Information Management, Katholieke Universiteit Leuven, 2006.

[6] MARTENS D., BAESENS B., VAN GESTEL T., VANTHIENEN J., Comprehensible credit

scoring models using rule extraction from support vector machines, Research Report

2 Note that most of the research reports have also been published as conference or journal paper.


0581, Department of Decision Sciences and Information Management, Katholieke

Universiteit Leuven, 2005.

[7] VAN GESTEL T., ESPINOZA M., BAESENS B., SUYKENS J.A.K., BRASSEUR C., DE MOOR

B., A Bayesian Nonlinear Support Vector Machine Error Correction Model, Internal

Report 04-140, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2004.

[8] VAN GESTEL T., BAESENS B., VAN DIJCKE P., GARCIA J., SUYKENS J.A.K., VANTHIENEN

J., A process model to develop an internal rating system: sovereign credit ratings,

Internal Report 04-130, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2004.

[9] VAN GESTEL T., Baesens B., Suykens J.A.K., Van den Poel D., Baestaens D.E.,

Willekens M., Bayesian Kernel-Based Classification for Financial Distress Detection,

Working Paper 04/247, Department of Marketing, Ghent University (Ghent, Belgium),

2004.

[10] MUES C., BAESENS B., FILES C.M., VANTHIENEN J., Decision Diagrams in Machine

Learning: an Empirical Study on Real-Life Credit-Risk Data, Technical report nr 0405,

ETEW, KU Leuven (Leuven, Belgium), 2004.

[11] BAESENS B., VERSTRAETEN G.,VAN DEN POEL D., EGMONT-PETERSEN M., VAN

KENHOVE P., VANTHIENEN J., Bayesian Network Classifiers for Identifying the Slope of

the Customer-Lifecycle of Long-Life Customers, Working Paper 02/154, Department of

Marketing, Ghent University (Ghent, Belgium), 2002.

[12] VAN GESTEL T., BAESENS B., SUYKENS J., BAESTAENS D., WILLEKENS M., VANTHIENEN

J., DE MOOR B., Bayesian Kernel Based Classification for Financial Distress Detection,

Internal Report 02-127, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2002.

[13] VAN GESTEL T., BAESENS B., SUYKENS J., BAESTAENS D., VANTHIENEN J., DE MOOR B.,

Bankruptcy Prediction with Least Squares Support Vector Machine Classifiers, Internal

Report 02-112, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2002.

[14] BAESENS B., EGMONT-PETERSEN M., CASTELO R., VANTHIENEN J., Learning Bayesian

network classifiers for credit scoring using Markov Chain Monte Carlo search,

Technical report UU-CS-2001-58, Institute of Computer and Information Sciences,

Utrecht University (Utrecht, The Netherlands), 2001.

[15] VIAENE S., BAESENS B., VAN DEN POEL D., VANTHIENEN J., DEDENE G., Bayesian

Neural Network Learning for Repeat Purchase Modelling in Direct Marketing, Working

Paper 01/105, Department of Marketing, Ghent University (Ghent, Belgium), 2001.


VANTHIENEN J., DE MOOR B., DEDENE G., Knowledge Discovery in a Direct Marketing

Case using Least Squares Support Vector Machines, Working Paper 01/104,

Department of Marketing, Ghent University (Ghent, Belgium), 2001.

[17] VIAENE S., BAESENS B., VAN DEN POEL D., DEDENE G., VANTHIENEN J., Wrapped Input

Selection using Multilayer Perceptrons for Repeat-Purchase Modeling in Direct

Marketing, Working Paper 01/102, Department of Marketing, Ghent University (Ghent,

Belgium), 2001.

Papers/wp_01_105.pdf









VANTHIENEN J., An Empirical assessment of Kernel Type Performance for Least

Squares Support Vector Machine Classifiers, Internal Report 00-52, ESAT-SISTA, KU

Leuven (Leuven, Belgium), 2000.

[19] VAN GESTEL T., SUYKENS J., BAESENS B., VIAENE S., VANTHIENEN J., DEDENE G., DE

MOOR B., VANDEWALLE J., Benchmarking Least Squares Support Vector Machine

Classifiers, Internal Report 00-37, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2000.


VANTHIENEN J., DE MOOR B., DEDENE G., Knowledge Discovery using Least Squares

Support Vector Machine Classifiers: a Direct Marketing Case, Internal Report 00-33,

ESAT-SISTA, KU Leuven (Leuven, Belgium), 2000.

[21] VIAENE S., BAESENS B., VAN GESTEL T., SUYKENS J.A.K., DEDENE G., DE MOOR B.,

VANTHIENEN J., Least Squares Support Vector Machine Classifiers : An empirical

evaluation, Internal Report 00-03, ESAT-SISTA, KU Leuven (Leuven, Belgium), 2000.

[22] VIAENE S., BAESENS B., VAN DEN POEL D., VANTHIENEN J., DEDENE G., Bayesian

Neural Network Learning for Repeat Purchase Modelling in Direct Marketing,

Technical report nr 0114, ETEW, KU Leuven (Leuven, Belgium), 2000.

[23] VIAENE S., BAESENS B., VAN DEN POEL D., DEDENE G., VANTHIENEN J., Wrapped

Feature Selection for Neural Networks in Direct Marketing, Technical report nr 0019,

ETEW, KU Leuven (Leuven, Belgium), 2000.


Technical report nr 0020, ETEW, KU Leuven (Leuven, Belgium), 2000.


VANTHIENEN J., Least Squares Support Vector Machine Classifiers: An Empirical

Evaluation, Technical report nr 0003, ETEW, KU Leuven (Leuven, Belgium), 2000.

[26] VIAENE S., BAESENS B., DEDENE G., VANTHIENEN J., VANDENBULCKE J., Sensitivity

Based Pruning of Input Variables by means of Weight Cascaded Retraining, Technical

report nr 9954, ETEW, KU Leuven (Leuven, Belgium), 1999.

Presentations

[1] BAESENS B., Social Networks for Data Mining, keynote talk, SAS Analytics 2011

conference, Orlando, US, October 24th-25th, 2011.

[2] BAESENS B., New Trends in Customer Analytics, 10th Annual Advanced Analytics and

Predictive Modeling Forum, The Institute for Health and Business Insight, Central

Michigan University, May 12th, 2011.

[3] BAESENS B., Data Mining in the Financial Services Industry: Change we Need, keynote

talk, SAS M2009 Conference, Las Vegas, United Sates, 26-27, October 2009.

[4] BAESENS B., Frontiers in Data Mining: Emerging Trends, Challenges and Applications,

keynote talk, SAS M2008 Conference, Las Vegas, United States, October 27 -28, 2008.


[5] BAESENS B., A backtesting and benchmarking framework for Basel II, School of

Management, University of Edinburgh, United Kingdom, June 22nd, 2007.

[6] BAESENS B., Trends in Data Mining: Emerging trends, challenges and applications,

Ecole de Gestion, Université de Liège, May 15th, 2007.

[7] BAESENS B., Data Mining: Emerging Trends, Challenges and Applications, Belgian

Statistical Society meeting, Houffalize, October 13th, 2006 (invited speaker).

[8] BAESENS B., Developing interpretable data mining decision models for Credit Risk,

Saïd Business School, Oxford, United Kingdom, June 29th, 2006.

[9] BAESENS B., Validating Basel II Models, Department of Economics and Finance, City

University of Hong Kong, Hong Kong, April 10th, 2006.

[10] BAESENS B., Data Mining on the Web, CORMSIS Seminar, School of Management,

University of Southampton, United Kingdom, October 28th, 2005.

[11] BAESENS B., Other approaches to credit scoring, OR Society, Birmingham, United

Kingdom, October 12th, 2005.

[12] BAESENS B., New Applications and Techniques in Data Mining, OR47 Conference,

Chester, United Kingdom, September 15th , 2005.

[13] BAESENS B., Validating Basel II Models, Infoline Workshop on Validating & Stress

testing Retail Portfolios, London, September 12th, 2005.

[14] BAESENS B., New Trends and Applications in Data Mining, CORMSIS Seminar, School

of Management, University of Southampton, United Kingdom, February 18th, 2005.

[15] BAESENS B., Beyond Basel II, Studiecentrum voor Automatische Informatieverwerking

(SAI), workshop on Credit Scoring and Basel II, Sodehotel, Woluwe, October 18th,

2004.

[16] BAESENS B., New Trends and Applications in Data Mining, SAS Forum Belgium &

Luxembourg, Aula Magna, Louvain-La-Neuve, October 14th, 2004.

[17] BAESENS B., Using Data Mining Techniques For Developing Credit-Risk Evaluation

Models, School of Design, Engineering and Computing, University of Bournemouth,

United Kingdom, July 13th, 2004.

[18] BAESENS B., Advanced Issues and Case Studies in data mining, Universitair Centrum

voor Statistiek (UCS), Leuven, Belgium, May 7th, 2004.

[19] BAESENS B., Modelling Challenges in the Context of Basel II, SAS Credit Scoring

Seminar, SAS, Tervuren, April 20th, 2004. Best Speaker


Models, IS Seminar, School of Computing, University of Singapore, Singapore,

October 29th, 2003.

[21] BAESENS B., Neural network survival analysis for Personal Loan Data, Credit Scoring

Workshop, Leuven, Belgium, September 26th, 2003.



Models, CISA seminar, Centre for Intelligent Systems and their Applications,

University of Edinburgh, Edinburgh, September 5th, 2003.


Models, Centre for Economic Research (CentER), Tilburg University, Tilburg, the

Netherlands, June 12th, 2003.

[24] BAESENS B., Web Mining for an On-Line Wine Selling Company using SAS Enterprise

Miner, SAS Academic Day, Flagey, Brussels, Belgium, May 15th, 2003.

[25] BAESENS B., Developing Business Intelligence Solutions For Credit-Risk Evaluation,

Contactgroep Beleidsinformatica (CBL), Credit Scoring Workshop, Leuven, Belgium,

March 11th, 2003.


Models, Ateliers de statistique appliquée, Institut de statistique, Université catholique de

Louvain-la-Neuve, Louvain-la-Neuve, Belgium, January 31st, 2003.

[27] BAESENS B., Knowledge Discovery Technieken voor Credit Scoring, Leuven Institute

for Research in Information Systems (LIRIS) meeting, Auberge du Pêcheur, Gent,

Belgium, December 9th, 2002.

[28] BAESENS B., Developing Intelligent Credit-Risk Solutions using Neural Network Rule

Extraction and Survival Analysis in SAS, The SAS Belgium & Luxembourg Users

(BLUES) Conference, Brabanthal, Haasrode, Belgium, October 24th, 2002. Best

Speaker Award

[29] BAESENS B., An Overview of Association Rule Mining, Universitair Centrum voor

Statistiek (UCS), Leuven, Belgium, September 3rd, 2002.

[30] BAESENS B., Knowledge Discovery in Data, Universitair Centrum voor Statistiek

(UCS), Leuven, Belgium, September 3rd, 2002.

[31] BAESENS B., Predicting Customer Default Times using Survival Analysis Methods in

SAS, SAS SEUGI, Palais des congrès, Paris, France, 13 juni 2002. Elected as SAS

Student Ambassador

[32] BAESENS B., Developing Intelligent Credit-Risk Solutions using SAS Enterprise Miner,

SAS Academic Day, La Tentation, Brussels, Belgium, May 23rd, 2002. Best Speaker

Award

[33] BAESENS B., An Overview of Association Rule Mining, Universitair Centrum voor

Statistiek (UCS), Leuven, Belgium, January 15th, 2002.

[34] BAESENS B., Knowledge Discovery in Data, Universitair Centrum voor Statistiek

(UCS), Leuven, Belgium, January 14th, 2002

[35] BAESENS B., Knowledge Discovery in Data: van academische denkoefening naar

bedrijfsrelevante praktijk, Studiecentrum voor Automatische Informatieverwerking

(SAI), avondconferentie, KBC, Leuven, Belgium, October 8th, 2001.

http://www.informatics.ed.ac.uk/research/cisa/


[36] BAESENS B., VIAENE S., A Bird’s Eye View on Business Intelligence, I+M seminarie,

Faculty Club, Leuven, Belgium, March 15th, 2001.

[37] BAESENS B., Knowledge Discovery in Data: van academische denkoefening naar

bedrijfsrelevante praktijk, Leuven Institute for Research in Information Systems

(LIRIS) meeting, Sodehotel, Woluwe, Belgium, December 11th, 2000.

[38] BAESENS B., VIAENE S., A Bird’s Eye View on Business Intelligence, I+M seminarie,

Hogenheuvelcollege, Leuven, , Belgium, March 16th, 2000.

[39] BAESENS B., Internet en Urologie, Lokale Kwaliteitscontrole, Urologen Noord West

Vlaanderen, AZ Sint-Jan, Bruges, Belgium, April 26th, 1999.

Documents

Curriculum Vitae Bart Baesens - KU Leuven · Curriculum Vitae B. Baesens 3 I was a member of the program committee of the Eighth International Conference on Enterprise Information