Dr. Vladimir Manewitsch

Senior Researcher

Vladimir Manewitsch works on the development and testing of data analysis methods in the context of market decisions. Currently, his research concentrates on the methods of artificial intelligence, in particular on causal analytical approaches. The aim is to detect and analyze relevant mechanisms by using data and behavioral analysis - with a special focus on decisions of consumers and companies.

Recent Projects:

• Bayesian Networks and causal graphs for driver analysis
• Marketing-Mix-Modelling with customer panel data (GfK-Brand Simulator)
• Discrete choice models: Evaluation of conjoint designs
• Automatic detection of emotions from facial expressions
• Development and implementation of segmentation approaches

Short CV:

• GfK Verein, Fundamental Research (Focus: Statistiscal methods)
• GfK SE, Data Science
• PhD (Dr. rer. pol.) in Economics at University Erlangen-Nuremberg with focus on multivariate statistics, missing data analysis and causal inference
• Diploma in Economics, University Kiel

Publications:

Lipovetsky, S., & Manewitsch, V. (2018). Analytical Closed-Form Solution for General Factor with Many Variables. Journal of Modern Applied Statistical Methods,17(2), Forthcoming.
Manewitsch, V. (2013). Statistische Methoden zur Analyse von Daten mit strukturell fehlenden Werten:  Mit Anwendungen aus der Marktforschung.  Dissertation, Universitätsbibliothek der Universität Erlangen-Nürnberg.