Marcel Schubert

Research Fellow IMPRS

Marcel H. Schubert is a doctoral researcher jointly positioned at the Faculty of Management, Economics, and Social Sciences at the University of Cologne and the Max-Planck-Institute for Research on Collective Goods in Bonn.
Marcel holds a BSc in Economics from the Ludwig-Maximilians University Munich which he completed in early 2015. In his thesis he focused on the advent of neuroeconomics and the insights new neuroscanning technology might be able to generate in regards to economic decision making.
Afterwards he spent time in a management consultancy, gaining practical experience in transformational processes required for what is commonly referred to as Industry 4.0.
In late 2015, he went back to university for a postgraduate studies. He finished his MSc in Economics at the University of Bonn in 2017. His master thesis focused the influence of language and grammar on the outcome of decisions in economic choice situations. Moreover, at the same time he completed a BSc in Computer Science, focusing on Machine Learning and IT Security. In 2019, he finished a second MSc in Cyber Security at the University of Lancaster. The final thesis focused on pinning down causal links between input used and the identification of humans made by algorithms in an online environment. During all his studies Marcel was funded by the Konrad-Adenauer scholarship.
In 2017 Marcel joined the Cologne Graduate School where his research project is supervised by Professor Fochmann. Keeping with the interest of his studies of furthering the field with new methods and insights from other disciplines, the main focus of his doctoral research is on finding ways to leverage data science and machine learning in the field of economics. The goal is to find new, data driven models for human behaviour. Some of his current projects in this regard focus on the use of Natural Language Processing for structuring and processing non-numeric data, such as legal texts, in new ways. Besides this, he is particularly interested in predicting economic behavior in group situations, the goal being to understand how group composition and individual factors affect the group outcome.

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