Prof. dr. Bart Baesens is a professor of Big Data and Analytics at KU Leuven (Belgium) and a lecturer at the University of Southampton (United Kingdom). He has done extensive research on Big Data & Analytics, Credit Risk Modeling, Fraud Detection and Marketing Analytics. He has written more than 200 scientific papers, some of which have been published in well-known international journals (e.g., MIS Quarterly, Machine Learning, Management Science, MIT Sloan Management Review and IEEE Transactions on Knowledge and Data Engineering) and presented at top international conferences (e.g., ICIS, KDD, CAISE). He has received various best paper and best speaker awards. Bart is the author of 8 books: Credit Risk Management: Basic Concepts (Oxford University Press, 2009), Analytics in a Big Data World (Wiley, 2014), Beginning Java Programming (Wiley, 2015), Fraud Analytics using Descriptive, Predictive and Social Network Techniques (Wiley, 2015), Credit Risk Analytics (Wiley, 2016), Profit Driven Business Analytics (Wiley, 2017), Web Scraping for Data Science using Python (Apress, 2018) and Principles of Database Management (Cambridge University Press, 2018). He sold more than 20.000 copies of these books worldwide, some of which have been translated in Chinese, Russian, Kazakh and Korean. His research is summarized at www.dataminingapps.com. He also regularly tutors, advises and provides consulting support to international firms regarding their big data, analytics and credit risk management strategy.

He also provides his own ON-LINE learning BlueCourses platform www.bluecourses.com offering courses on Machine Learning, Fraud Analytics, Customer Lifetime Value Modeling, Recommender Systems and Text Analytics.

Next to his professional activities, Bart is obsessed by reading books and visiting sites related to World War I and II. He is espeically fascinated by Winston Churchill. He is also a true soccer fan and loves travelling, international food and wine tasting!

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Wouter Verbeke, Ph.D., is an assistant professor of data analytics and business informatics at Vrije Universiteit Brussel (Belgium). He graduated in 2007 as a Civil civil Engineer engineer and obtained a Ph.D. in applied economics at KU Leuven (Belgium) in 2012. In 2013, he joined VU Brussel were he founded and leads the data analytics laboratory (www.data-lab.be).

His research is mainly situated in the field of predictive, prescriptive, and network analytics, and is driven by real-life business problems, including applications in customer relationship, credit risk, fraud, supply chain, and human resources management. Specifically, his research focuses on taking into account costs and benefits in developing and evaluating business analytics applications. Another key research topic is uplift modeling and prescriptive analytics. Wouter teaches several courses on information systems and advanced modeling for decision making to business students, and provides training to business practitioners on customer analytics, credit risk modeling, and fraud analytics. He has been setting up and carrying out research projects with a range of companies from the financial, ICT, and HR services industry.

His work has been published in established international scientific journals such as IEEE Transactions on Knowledge and Data Engineering, European Journal of Operational Research, and Decision Support Systems. He is also author of the book Fraud Analytics Using Descriptive, Predictive & Social Network Techniques —The essential guide to Data Science for Fraud Detection, published by Wiley in 2015, and the book Profit-Driven Business Analytics, published by Wiley in September 2017. In 2014, he won the distinguished EURO award for best article published in the European Journal of Operational Research in the category “Innovative Applications of O.R.”

Véronique Van Vlasselaer graduated magna cum laude as Master Information Systems Engineer at the faculty of Business and Economics, KU Leuven (Belgium). For her master thesis topic "Mining Data on Twitter", she received the best thesis award from the faculty's student branch.

In October 2012, Véronique started as Ph.D researcher with prof. Bart Baesens at the department of Decision Sciences and Information Management. Her main research topics include social network analysis, fraud detection and net lift modeling.