Dries Benoit obtained a PhD in Applied Economics (Data Analytics) in 2011 from Ghent University.
Currently, he is associate professor in Data Analytics at Ghent University and teaches Bayesian Statistics, Statistical Modeling & Datamining and Pricing & Revenue Management to the students in Business Engineering.
|He is also visiting professor at Université de Namur (Namur, Belgium) and IESEG School of Management (Lille||Paris, France).|
Dries Benoit specializes in Bayesian Statistics: an alternative (to frequentist statistics) paradigm for doing inference, prediction and model selection.
He works on both methodological as well as applied problems, where most applications are in the field of business administration and management (marketing, fincance, operations research).
As a data-scientist, he often work together with researcher from other fields such as medicine, energy, education, etc.
Keywords: Bayesian Statistics, marketing modeling, customer relationship management, learning analytics
Benoit, Dries, & Van den Poel, D. (2017). bayesQR : a Bayesian approach to quantile regression. JOURNAL OF STATISTICAL SOFTWARE , 76(7), 1–32.
Sadeghianpourhamami, N., Demeester, T., Benoit, D., Strobbe, M., & Develder, C. (2016). Modeling and analysis of residential flexibility: timing of white good usage. APPLIED ENERGY, 179, 790–805.
Benoit, Dries, Alhamzawi, R, Yu, K. (2013). Bayesian lasso binary quantile regression. Computational Statistics, 28(6), 2861-2873.
Oosterlinck, D., Benoit, D., Baecke, P., & Van de Weghe, N. (2017). Bluetooth tracking of humans in an indoor environment : an application to shopping mall visits. APPLIED GEOGRAPHY, 78, 55–65.
Roelens, I., Baecke, P., & Benoit, D. (2016). Identifying influencers in a social network : the value of real referral data. DECISION SUPPORT SYSTEMS, 91, 25–36