Seppe vanden Broucke

Born: 9-Nov-1986
Leuven, Belgium
+32 (0)497 126781
seppe@seppe.net
http://seppe.net

Profile

Seppe vanden Broucke received a PhD in Applied Economics at KU Leuven, Belgium in 2014. Currently, Seppe is working as an assistant professor at the department of Decision Sciences and Information Management at KU Leuven. Seppe's research interests include business data mining and analytics, machine learning, process management, process mining. His work has been published in well-known international journals and presented at top conferences.

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Publications

Articles in Internationally Reviewed Academic Journals

Höppner S., Stripling E., Baesens B., vanden Broucke S., Verdonck T. (2018). Profit Driven Decision Trees for Churn Prediction. European Journal of Operational Research, accepted.

Wang, Y., Huang, L., vanden Broucke, S. (2018). An activity theory based approach for ontological modelling of collaborative logistics process dynamics. International Journal of Logistics, Taylor & Francis, 1367-5567.

Lemahieu, W., Vanden Broucke, S., & Baesens, B. (2018). An Interview with Bart Baesens, One of the Authors of Principles of Database Management. Big Data, 6(2), 69-71.

Nelissen K., Snoeck M., vanden Broucke S., Baesens B. (2018). Swipe and tell: using implicit feedback to predict user engagement on tablets. ACM Transactions on Information Systems.

Stripling, E., Vanden Broucke, S., Antonio, K, Baesens, B, & Snoeck, M. (2018). Profit maximizing logistic model for customer churn prediction using genetic algorithms. Swarm and Evolutionary Computation, 40, 116-130.

Ponce de Leon H., Nardelli L., Carmona J., vanden Broucke S. (2018). Incorporating negative information to process discovery of complex systems. Information Sciences, 422, 480-496.

Lismont J., Van Calster T., Oskarsdottir M., vanden Broucke S., Baesens B., Lemahieu W., Vanthienen J. (2018). Closing the gap between experts and novices using analytics-as-a-service: an experimental study. Business & Information Systems Engineering.

Stripling E., Baesens B., Chizi B., vanden Broucke S. (2018). Isolation-based conditional anomaly detection on mixed-attribute data to uncover workers' compensation fraud. Decision Support Systems.

Zhu, B., Baesens, B., Backiel, A., vanden Broucke, Seppe KLM. (2018). Benchmarking sampling techniques for imbalance learning in churn prediction. Journal of the Operational Research Society, 69(1), 49-65.

vanden Broucke S., De Weerdt J. (2017). Fodina: a Robust and Flexible Heuristic Process Discovery Technique. Decision Support Systems, 100, 109-118.

De Koninck P., De Weerdt J., vanden Broucke S. (2017). Explaining clusterings of process instances. Data Mining and Knowledge Discovery, 31 (3), 774-808.

Zhu B., Baesens B., vanden Broucke S. (2017). An empirical comparison of techniques for the class imbalance problem in churn prediction. Information Sciences, 408, 84-99.

Low W., vanden Broucke S., Wynn M., ter Hofstede A., De Weerdt J., van der Aalst W. (2016). Revising history for cost-informed process improvement. Computing, 98 (9), 895-921.

vanden Broucke, S., Caron, F., Lismont, J., Vanthienen, J., Baesens, B. (2016). On the gap between reality and registration: a business event analysis classification framework. Information Technology & Management, 17 (4), 393-410.

Zhu, X., vanden Broucke, S., Zhu, G., Vanthienen, J., Baesens, B. (2016). Enabling flexible location-aware business process modeling and execution. Decision Support Systems, (83), 1-9.

Lismont, J., Janssens, A., Odnoletkova, I., vanden Broucke, S., Caron, F., Vanthienen, J. (2016). A guide for the application of analytics on healthcare processes: a dynamic view on patient pathways. Computers in Biology and Medicine, 77, art.nr. S0010-4825(16)30198-6, 125-134.

Zhu, X., Zhu, G., vanden Broucke, S. (2015). 地理空间约束的业务流程建模方法. Ruanjian Xuebao (Journal of Software) 《计算机集成制造系统》期刊, 26 (3), 584-599, ISSN l000-9825.

vanden Broucke, S., De Weerdt, J., Vanthienen, J., Baesens, B. (2014). Determining process model precision and generalization with weighted artificial negative events. IEEE Transactions on Knowledge and Data Engineering, 26 (8), 1877-1889.

Seret, A., vanden Broucke, S., Baesens, B., Vanthienen, J. (2014). A dynamic understanding of customer behavior processes based on clustering and sequence mining. Expert Systems with Applications, 41 (10), 4648-4657.

De Weerdt, J., vanden Broucke, S., Vanthienen, J., Baesens, B. (2013). Active trace clustering for improved process discovery. IEEE Transactions on Knowledge and Data Engineering, 25 (12), 2708-2720.

Van den Bulcke, T., Vanden Broucke, P., Van Hoof, V., Wouters, K., vanden Broucke, S., Smits, G., Smits, E., Proesmans, S., Van Genechten, T., Eyskens, F. (2011). Data mining methods for classification of Medium-Chain Acyl-CoA dehydrogenase deficiency (MCADD) using non-derivatized tandem MS neonatal screening data. Journal of Biomedical Informatics, 44 (2), 319-325.

Articles in International Scientific Conferences and Symposia

Reynkens, T., Antonio, K., Devriendt, S., Baesens, B., Vanden Broucke, S. (2018). Network-based fraud detection in insurance using GOTCHA! 4th European Actuarial Journal Conference, Leuven, Belgium.

De Koninck, P., vanden Broucke, S., De Weerdt, J. (2018). act2vec, trace2vec, log2vec, and model2vec: Representation learning for Business Processes. Proceeding of the 16th International Conference on Business Process Management (BPM 2018). Sydney (Australia), 9-14 September 2018.

Stripling, E., Baesens, B., vanden Broucke, S. (2018). Regularized Empirical EMP Maximization Framework for Profit-Driven Model Building. Workshop on Utility-Driven Mining in conjunction with the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Date: August 19 - 23, 2018. London, United Kingdom.

Höppner S., Stripling E., Baesens B., vanden Broucke S., Verdonck T. (2018). Profit Driven Decision Trees for Churn Prediction, Proceedings of the conference on Data Science, Statistics and Visualisation (DSSV 2018), Vienna, Austria, July 9-11, 2018.

Stripling E., Baesens B., vanden Broucke S. (2018). Building profit-sensitive classifiers for maximum profit: vol. accepted. European Conference on Operational Research (EURO 2018). Valencia (Spain), 8-11 July 2018.

Devos, A., Dhondt, J., Stripling, E., Baesens, B., vanden Broucke, S., Sukhatme, G. (2018). Profit Maximizing Logistic Regression Modeling for Credit Scoring. IEEE Data Science Workshop (IEEE DSW 2018). Lausanne (Switzerland) 4-6 June 2018.

De Smedt, J., Hasic, F., vanden Broucke, S., Vanthienen, J. (2017). Towards a Holistic Discovery of Decisions in Process-Aware Information Systems. Proceeding of the 15th International Conference on Business Process Management (BPM 2017). Barcelona (Spain), 10-15 September 2017.

Haupt J., Stripling E., Baesens B., vanden Broucke S., Lessmann S. (2017). Profit-maximizing scorecard development. Credit Scoring and Credit Control XV Conference. Edinburgh (Scotland), 30 August - 1 September 2017.

De Koninck P., Nelissen K., Baesens B., vanden Broucke S., Snoeck M., De Weerdt J. (2017). An approach for incorporating expert knowledge in trace clustering. International Conference on Advanced Information Systems Engineering (CAiSE 2017). Essen (Germany), 12-16 June 2017.

De Smedt J., vanden Broucke S., Obregon J., Kim A., Jung JY., Vanthienen J. (2017) Decision Mining in a Broader Context: An Overview of the Current Landscape and Future Directions. In: Dumas M., Fantinato M. (eds) Business Process Management Workshops. BPM 2016. Lecture Notes in Business Information Processing, vol 281. Rio de Janeiro (Brazil), 18-22 September 2016, Springer.

Van Calster, T., Lismont, J., Oskarsdottir, M., vanden Broucke, S., Vanthienen, J., Lemahieu, W., Baesens, B. (2016). Automated analytics: the organizational impact of analytics-as-a-service. Proceedings of the EI-KDD’16 workshop: Vol. accepted. Workshop on Enterprise Intelligence in conjunction with 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. San Francisco (US), 14 August 2016.

vanden Broucke, S., Vanthienen, J., De Smedt, J. (2015). Student Journey Mapping: Learning Analytics in Action. Efficiency in Education and the use of Big data. Leuven (Belgium), 19-20 November 2015.

Stripling, E., vanden Broucke, S., Antonio, K., Baesens, B., Snoeck, M. (2015). Profit maximizing logistic regression modeling for customer churn prediction. IEEE International Conference on Data Science and Advanced Analytics (DSAA' 2015). Paris (France), 19-21 October 2015.

Ponce-de-Leon, H., Carmona, J., vanden Broucke, S. (2015). Incorporating negative information in process discovery. Proceeding of the 13th International Conference on Business Process Management (BPM 2015). Innsbruck (Austria), 31 August - 3 September 2015.

Zhu, X., Zhu, G., vanden Broucke, S. (2014). 地理空间约束的业务流程建模方法. 第四届中国业务过程管理大会 (China BPM 2014). Shanghai, China, 17 October 2014.

vanden Broucke, S., Muñoz-Gama, J., Carmona, J., Baesens, B., Vanthienen, J. (2014). Event-based real-time decomposed conformance analysis, 18 pp. OnTheMove Federated Conferences & Workshops, CoopIS 2014 (CoopIS'14), Amantea, Calabria (Italy), 27-31 October 2014.

Zhu, X., Zhu, G., vanden Broucke, S., Vanthienen, J., Baesens, B. (2014). Supporting Sustainable Business Processes through a Geospatial Context Extension. 2nd International Conference on Geo-Informatics in Resource Management & Sustainable Ecosystem (GRMSE'14). Michigan (USA), 3-5 October 2014.

Zhu X., Zhu G., vanden Broucke, S., Vanthienen, J., Baesens, B. (2014). Towards Location-Aware Process Modeling and Execution. Workshop on Data- & Artifact- centric BPM (DAB'14). Haifa (Israel), 7-11 September 2014.

De Weerdt, J., vanden Broucke, S., Caron, F. (2014). Bidimensional Process Discovery for Mining BPMN Models. Workshop on Decision Mining & Modeling for Business Processes (DeMiMoP’14). Haifa (Israel), 7-11 September 2014.

De Weerdt, J., vanden Broucke, S., Vanthienen, J., Baesens, B. (2014). Explaining Clustered Process Instances, Business Process Management Conference 2014, Haifa (Israel), 7-11 September 2014.

vanden Broucke, S., Vanthienen, J., Baesens, B. (2014). Declarative Process Discovery with Evolutionary Computing. 2014 IEEE Congress on Evolutionary Computation Proceedings: Vol. accepted. 2014 IEEE. Beijing (China), 6-11 July 2014.

Low, W.Z., De Weerdt, J., ter Hostede, A.H.M., van der Aalst, W.M.P., vanden Broucke, S. (2014). Cost Optimisation of Business Process Execution. 2014 IEEE Congress on Evolutionary Computation Proceedings: Vol. accepted. 2014 IEEE. Beijing (China), 6-11 July 2014.

vanden Broucke, S., Vanthienen, J., Baesens, B. (2013). Volvo IT Belgium VINST. Proceedings of the 3rd Business Process Intelligence Challenge co-located with 9th International Business Process Intelligence workshop (BPI 2013): Vol. 1052. Business Process Intelligence Challenge 2013 (BPIC 2013). Beijing (China), 26 August 2013 (art.nr. 3). Aachen (Germany): RWTH Aachen University.

vanden Broucke, S., Caron, F., Vanthienen, J., Baesens, B. (2013). Validating and enhancing declarative business process models based on allowed and non-occurring past behavior. Business Process Management Workshops. Workshop on Decision Mining & Modeling for Business Processes (DeMiMoP’13). Beijing (China), 26-30 August 2013.

vanden Broucke, S., Delvaux, C., Freitas, J., Rogova, T., Vanthienen, J., Baesens, B. (2013). Uncovering the relationship between event log characteristics and process discovery techniques. Business Process Management Workshops. Workshop on Business Process Intelligence (BPI2013). Beijing (China), 26-30 August 2013.

Seret, A., vanden Broucke, S., Baesens, B., Vanthienen, J. (2013). An exploratory approach for understanding customer behavior processes bases on clustering and sequence mining. Business Process Management Workshops. Workshop on Decision Mining & Modeling for Business Processes (DeMiMoP’13). Beijing (China), 26-30 August 2013.

vanden Broucke, S., De Weerdt, J., Vanthienen, J., Baesens, B. (2013). A comprehensive benchmarking framework (CoBeFra) for conformance analysis between procedural process models and event logs in ProM. Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2013, part of the IEEE Symposium Series on Computational Intelligence 2013, SSCI 2013: vol. accepted. IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2013). Singapore, 16-19 April 2013.

Caron, F., vanden Broucke, S., Vanthienen, J., Baesens, B. (2012). On the distinction between truthful, invisible, false and unobserved events. Sprouts: Working Papers on Information Systems: vol. 12 (16). 11th JAIS Theory Development Workshop at ICIS 2012. Orlando, Florida, 16 December 2012.

Caron, F., vanden Broucke, S., Vanthienen, J., Baesens, B. (2012). On the distinction between truthful, invisible, false and unobserved events.

Proceedings of the 18th Americas Conference on Information Systems: Vol. e-pub. Americas Conference on Information Systems. Seattle, Washington (US), 9-12 August 2012 (art.nr. 24) Association for Information Systems.

De Weerdt, J., vanden Broucke, S., Vanthienen, J., Baesens, B. (2012). Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes. Evolutionary Computation (CEC), 2012 IEEE Congress on. Congress on Evolutionary Computation (CEC), 2012 IEEE. Brisbane (Australia), 10-15 June 2012 (pp. 1-8) IEEE computational intelligence society.

vanden Broucke, S., De Weerdt, J., Baesens, B., Vanthienen, J. (2012). An improved artificial negative event generator to enhance process event logs. In Ralyt, J. (Ed.), Franch, X. (Ed.), Brinkkemper, S. (Ed.), Wrycza, S. (Ed.), Lecture Notes in Computer Science. International Conference on Advanced Information Systems Engineering (CAiSE'12). Gdansk (Poland), 25-29 June 2012 (pp. 254-269) Springer.

Books and Book Chapters

vanden Broucke S., Baesens B. (2018). Practical Web Scraping for Data Science: Best Practices and Examples with Python. Apress.

Lemahieu W., vanden Broucke S., Baesens B. (2018). Principles of database management – the practical guide to storing, managing and analyzing small and big data. Cambridge University Press, forthcoming.

Baesens, B., Backiel, A., vanden Broucke, S. (2015). Java для начинающих. Объектно-ориентированный подход. Wrox. Wiley.

vanden Broucke S., Baesens B. (2018). Web scraping for data science with Python. CreateSpace Amazon.

De Smet J., Vanden Broucke S., Vanthienen J., De Witte K. (2017). Improved student feedback with process and data analytics. In: Vanthienen J., De Witte K. (Eds.), Data analytics applications in education, (pp. 11-37) Taylor and Francis.

Baesens, B., Backiel, A., vanden Broucke, S. (2015). Beginning Java: Object Oriented Programming for Business Applications. Wrox, Wiley.

Baesens, B. (2014). Chapter: Business Process Analytics by vanden Broucke S. in Analytics in A Big Data World: The Essential Guide to Data Science and its Applications. Wiley, June 2014.

Articles in Professionally Oriented Journals, Technical Reports, Science Outreach

Lemahieu, W., vanden Broucke, S., Baesens, B. (2018). Principles of Database Management: The Practical Guide to Storing, Managing and Analyzing Big and Small Data. KDnuggets.

Lemahieu, W., vanden Broucke, S., Baesens, B. (2018). Opinion: Building the ideal data quality team starts with these roles. September 25, 2018 Information-management.com.

Baesens, B., vanden Broucke, S., Lemahieu, W. (2018). Relational Databases vs. NoSQL Databases: The End of the One-Size-Fits-All Era? September 18, 2018, Cutter Consortium.

Lemahieu, W., vanden Broucke, S., Baesens, B. (2018). OLAP queries in SQL: A Refresher. KDnuggets.

Baesens, B., vanden Broucke, S., Lemahieu, W. (2018). Just in Case: A Database Perspective on Business Continuity. July 24, 2018, Cutter Consortium.

Lemahieu, W., vanden Broucke, S., Baesens, B. (2018). Opinion: SQL, NoSQL or NewSQL: How organizations can make the right pick. July 18, 2018 Information-management.com.

Baesens, B., Lemahieu, W., vanden Broucke, S. (2018). Opinion: How database management practices impact business continuity. June 11, 2018 Information-management.com.

Lemahieu, W., Baesens, B., vanden Broucke, S. (2018). To SQL Or Not To SQL: That’s The Question. DataScience.com.

Lemahieu, W., Baesens, B., vanden Broucke, S. (2018). To SQL Or Not To SQL: That’s The Question! Analytics India Magazine.

Lemahieu, W., vanden Broucke, S., Baesens, B. (2018). To SQL or not to SQL: that is the question! KDnuggets.

Baesens, B., vanden Broucke, S., Lemahieu, W. (2018). Big Data Experts: Top Job Titles. May 1, 2018, Datamation.

Baesens, B., vanden Broucke, S., Lemahieu, W. (2018). Data Integration Vs. Data Quality: Friends or Foes? May 1, 2018, Cutter Consortium.

Wells, J., vanden Broucke, S. (interviewee) (2017). Using Web Scraping as a Data Science Tool. Database Trends and Applications, 4/12/2017.

Van Sas, E.J., vanden Broucke, S. (interviewee) (2017). Voorbij de hype... Big data gaat volgende fase in. Financieel Management, 27/11/2017.

Vangelder, J., vanden Broucke, S. (interviewee) (2017). Geld verdienen met big data blijkt moeilijker dan gedacht. Trends, 31/08/17.

vanden Broucke, S., Baesens, B. (2017). Web Scraping for Data Science with Python. KDnuggets.

Zhu, B. Baesens, B., vanden Broucke, S. (2017). Do We Need Balanced Sampling? KDnuggets.

vanden Broucke, S. (2017). Process Mining with R: Introduction. KDnuggets.

vanden Broucke, S., De Weerdt, J. (2016). Van groot naar groots: toekomstige uitdagingen in big data en analytics. ECONnect 2016.

Baesens, B., Backiel, A., vanden Broucke, S. (2015). The State of Database Access in Java: Passchendaele revisited! Cutter IT Email Advisor, January 19, Cutter Consortium.

vanden Broucke, S., Baesens, B., Lismont, J., Vanthienen, J. (2014). Sluit de lus: moderne technieken in Business Process Analytics. Informatie.

Baesens, B., vanden Broucke, S., Dejaeger, K., Eerola, T., Goedhuys, L., Riis, M., Wehkamp, R. (2013). Cloudcomputing in analytics: de hype ontraadseld. Informatie.

vanden Broucke, S., Baesens, B., Vanthienen, J. (2013). Closing the loop: state of the art in business process analytics. Data Insight & Social BI: Executive Update, Cutter Consortium.

vanden Broucke, S. (2013). What’s in a name: Bitcoin, de digitale munteenheid. ECONnect (Q2), 40-41.

Dejaeger, K., vanden Broucke, S., Eerola, T., Wehkamp, R., Goedhuys, L., Riis, M., Baesens, B. (2012). Beyond the hype: cloud computing in analytics. Finland: Techila Technologies.

Dejaeger, K., vanden Broucke, S., Eerola, T., Wehkamp, R., Goedhuys, L., Riis, M., Baesens, B. (2012). Beyond the hype: cloud computing in analytics. Data Insight & Social BI: Executive Update, Cutter Consortium.

Ponce-de-Léon, H., Carmona, J., vanden Broucke, S. (2015). Incorporating negative information in process discovery. FEB Research Report KBI_1510, 17 pp. Leuven (Belgium): KU Leuven - Faculty of Economics and Business.

De Smedt, J., vanden Broucke, S., De Weerdt, J., Vanthienen, J. (2015). A full R/I-net construct lexicon for declare constraints. FEB Research Report KBI_1506, 20 pp. Leuven (Belgium): KU Leuven - Faculty of Economics and Business.

vanden Broucke, S., Vanthienen, J., Baesens, B. (2014). Straightforward Petri net-based event log generation in ProM. FEB Research Report KBI_1417, 12 pp. Leuven (Belgium): KU Leuven - Faculty of Economics and Business.

vanden Broucke, S., Muñoz-Gama, J., Carmona, J., Baesens, B., Vanthienen, J. (2013). Event-based real-time decomposed conformance analysis, 21 pp: Polytechnic University of Catalonia, Department of Information Languages and Systems.

vanden Broucke, S., De Weerdt, J., Vanthienen, J., Baesens, B. (2013). On replaying process execution traces containing positive and negative events. FEB Research Report KBI_1311, 17 pp. Leuven (Belgium): KU Leuven - Faculty of Economics and Business.

De Weerdt, J., vanden Broucke, S., Vanthienen, J., Baesens, B. (2012). Leveraging process discovery with trace clustering and text mining for intelligent analysis of incident management processes. FEB Research Report KBI_1215, 9 pp. Leuven (Belgium): KU Leuven - Faculty of Business and Economics.

vanden Broucke, S., De Weerdt, J., Vanthienen, J., Baesens, B. (2012). An improved process event log artificial negative event generator. FEB Research Report KBI_1216, 1-17 pp. Leuven (Belgium): KU Leuven - Faculty of Economics and Business.