Michel Ballings

Transcription

Michel Ballings
New items since Aug 1, 2014 are in blue
Michel Ballings
Assistant Professor of Business Analytics at The University of Tennessee
Department of Business Analytics and Statistics
235 Stokely Management Center
Knoxville, TN 37996-0525
mb@utk.edu
ballings.co
https://twitter.com/michelballings
http://www.linkedin.com/in/michelballings
Google Scholar: http://goo.gl/HGR1Vf
http://bas.utk.edu/our-department/faculty/ballings.asp
Summary
Assistant Professor of Business Analytics at The University of Tennessee, interested in machine learning and
predictive analytics for social media. Trained at the intersection of three disciplines: (a) statistics and machine
learning, (b) programming and computing, and (c) business, management and marketing.
Education
2008–2014
Ph.D. in Applied Economics, Ghent University
Title: Advances and Applications in Ensemble Learning
Supervisor: Prof. dr. Dirk Van den Poel (Dirk.VandenPoel@UGent.be)
2006–2008
Master in Business Economics, VLEKHO Business School Brussels
(Magna cum laude, Ranking: 1st)
2003–2006
Bachelor in Business Administration, Leuven University College
(Cum laude)
Studied at Haute Ecole d’Enseignement Sup´erieur de Namur (one semester, 2005)
Studied abroad at Universidad de M`alaga (one semester, 2005 - 2006)
Teaching
•UTK: The University of Tennessee, UGent: Ghent University
Fall 2014
•UTK: STAT 583, section 2: Marketing Analytics (R)
Spring 2014
•UGent: Marketing Models and Marketing Engineering (R)
Spring 2013
•UGent: Marketing Models and Marketing Engineering (R)
Fall 2012
•UGent: Marketing Information Systems - DB Marketing ((PL/)SQL, ODM)
Fall 2011
•UGent: Marketing Information Systems - DB Marketing ((PL/)SQL, ODM)
Fall 2010
•UGent: Marketing Information Systems - DB Marketing ((PL/)SQL, ODM)
•UGent:Analytical Customer Relationship Management (SAS)
Fall 2009
•UGent:Analytical Customer Relationship Management (SAS)
Fall 2008
•UGent:Analytical Customer Relationship Management (SAS)
Employment
2014–now
Assistant Professor of Customer Analytics at The University of Tennessee
2008–2014
Doctoral researcher and teaching assistant at Ghent University
2008–2010
Consultant at Psilogy
2007–2008
Internship at AB InBev
Languages
Dutch
Native speaker
English
Full professional proficiency
French
Full professional proficiency
Spanish
Elementary proficiency
Skills
Programming
R
SAS: BASE, STAT, MACRO
Oracle: SQL, PL/SQL, Data Mining (ODM)
SPSS-syntax
LISREL
Applications
Reporting
Predictive Analytics, Data Mining, Acquisition Modeling, Up-Sell Modeling, Cross-Sell Modeling, Retention Modeling, Segmenting Targeting Positioning, Out-of-stock prediction
MS Word, MS PowerPoint, MS Excel, LATEX
Software
2014
• Michel Ballings, and Dirk Van den Poel (2014). R package dummy: Automatic creation of
dummy variables with support for predictive modeling
2013
• Michel Ballings, and Dirk Van den Poel (2013). R package kernelFactory: an ensemble of
kernel machines.
• Dirk Van den Poel, Michel Ballings, Andrey Volkov, Jeroen D’haen, and Michiel Van Herwegen (2013). R package aCRM: convenience functions for analytical customer relationship
management.
• Michel Ballings, Dauwe Vercamer, and Dirk Van den Poel. Hybrid Ensemble: An R package
for Hybrid Ensemble classification)
• Michel Ballings, and Dirk Van den Poel. AUC: Threshold independent performance measures
for probabilistic classifiers
Conference Talks
2014
• Michel Ballings. CRM in Social Media: Predicting Increases in Facebook Usage Frequency.
INFORMS Annual Meeting 2014, Session Title: Predictive Analytics for Social Media, Cluster:
Artificial Intelligence, San Francisco, USA, November 9-12, 2014
2013
• Michel Ballings. Evaluating multiple weight estimation methods in hybrid ensembles. The
2nd Annual Conference of the Dutch/Flemish Classification Society (VOC), Antwerp, Belgium,
May 31, 2013
2012
• Michel Ballings. The dangers of using intention as a surrogate for retention in brand positioning decision support systems. The 36th Annual Conference of the German Classification
Society (GFKL), Hildesheim, Germany, August 1-3, 2012
• Michel Ballings. Improving customer churn prediction by data augmentation using pictorial stimulus-choice data. International Symposium on Management Intelligent Systems,
Salamanca, Spain, May 22-14, 2012
2011
• Michel Ballings. Data Augmentation in Customer Intelligence using Pictorials. 2011 Joint
Statistical Meetings, Miami, USA, July 30- August 4, 2011
Seminar Talks
2014
• Michel Ballings. Social Media Analytics. Seminar Talk. The University of Tennessee, Haslam
College of Business, Department of Management, November 4, 2014
• Michel Ballings. Advances in Social Media Analytics. Seminar Talk. The University of
Tennessee, College of Engineering, Department of Industrial and Systems Engineering, October
3, 2014
2012
• Michel Ballings. Resolutions to Having Too Much or Too Little Data. Top Management
aCRM Training, Ghent University, College of Economics and Business Administration, Department of Marketing, August 10, 2012.
2011
• Michel Ballings. Data Augmentation for CRM. Executive Course: Predictive Analytics
for Customer Intelligence in Financial Services, Ghent University, College of Economics and
Business Administration, Department of Marketing, August 18, 2011.
Practical industry projects
Analytics projects. Executed, coached or managed.
2014
• Hanes Brands Inc. (Project coach)
• Club Brugge
2013
• Essent (Project manager)
2012
• Concentra
2011
• USG People
2010
• Friesland Campina
2009, 2010
• Vodafone
• Carglass
2008
• Anheuser Busch InBev (internship project)
2014
• Faculty coach in BZAN 550 -Business Analytics Experience Capstone
Service
• Talk: The Twin Tools of Predictive Analytics and Testing, at FedEX Operation Research
and Management Science (FORMS) Conference in Memphis, University of Memphis, Sep 16
• Search committee member for two new Faculty members at the Assistant Professor level
Journal Articles
2013
• Michel Ballings and Dirk Van den Poel (2013). Kernel factory: An ensemble of kernel
machines. Expert Systems with Applications, 40(8), 2904-2913.
2012
• Michel Ballings and Dirk Van den Poel (2012). Customer event history for churn prediction:
How long is long enough? Expert Systems with Applications, 39(18): 13517-13522.
Conference Papers
2013
• Michel Ballings and Dirk Van den Poel (2013). Using Eye-Tracking Data of Advertisement
Viewing Behavior to Predict Customer Churn. In 2013 IEEE 13th International Conference
on Data Mining Workshops (ICDMW 2013), 7 December 2013, Dallas, Texas, USA.
• Michel Ballings and Dirk Van den Poel (2013). The dangers of using intention as a surrogate
for retention in brand positioning decision support systems. In M. Spiliopoulou and L. SchmidtThieme, editors, Studies in Classication, Data Analysis, and Knowledge Organization, page 8.
Hildesheim, Germany.
2012
• Michel Ballings, Dirk Van den Poel, and Emmanuel Verhagen (2012). Improving customer
churn prediction by data augmentation using pictorial stimulus-choice data. In J. Casillas, F.
J. Martinez Lopez, and J. M. Corchado, editors, Management Intelligent Systems, volume 171,
pages 217-226. Springer-Verlag Berlin, Berlin.
2011
• Michel Ballings, Dries F. Benoit, and Dirk Van den Poel (2011). RFM variables revisited
using quantile regression. In M. Spiliopoulou, W. Haixun, D. Cook, P. Jian, W. Wei, O. Zaiane,
and W. Xindong, editors, 2011 IEEE International Conference on Data Mining Workshops,
pages 1163-1169. Vancouver, Canada.
Professional Affiliations
Since 2014
• The Institute for Operations Research and the Management Sciences (INFORMS)
Since 2011
• Foundation for Open Access Statistics (FOAS)
Journal Reviews
Since 2014
• Omega, The International Journal of Management Science
• Expert Systems with Applications (ESWA)
Since 2013
• Journal of the Association for Information Science and Technology
Ph.D. students
Started 06/2014
• Co-advisor of Matthijs Meire. Topic: Big Data Marketing Analytics and Social Media. Ghent
University.
Started 09/2014
• Co-advisor of Steven Hoornaert. Topic: Social Media Analytics. Ghent University.
Started 09/2014
• Co-advisor of Matthias Bogaert. Topic: Social Media Analytics. Ghent University.