Dr. Sven KlaaßenAppointment at the University of Kiel

2 April 2026

Photo: UHH/Longe

Dr. Sven Klaaßen, a research assistant in the Department of Statistics, has accepted an appointment as a junior professor on a tenure-track position at the University of Kiel. To mark the occasion, we spoke to him about his experiences in his studies and research.

Dr. Sven Klaaßen, research assistant at the Professorship of Statistics under Prof. Dr. Martin Spindler, has accepted a position as a junior professor on a tenure track at Kiel University. From 1 May, he will be teaching statistics and empirical economic research there. As he leaves, we asked him about his experiences at the School.

Sven, how long have you been part of the School, both as a student and as a research assistant?

I started at the Business School as a research assistant in January 2017. Before that, I studied Mathematical Economics at the University of Hamburg.

What motivated you to decide to pursue a PhD?

I was driven above all by a fascination with machine learning and the enormous potential of modern algorithms in the analysis of complex datasets. The PhD offered me the academic freedom to delve deeply into these methodological questions and develop innovative solutions to real-world statistical problems.

You are an expert in the field of machine learning and have already produced numerous publications. What exactly is your favourite topic and what does it involve?

My focus is on combining machine learning with causal inference. Whilst traditional algorithms primarily operate as ‘black boxes’ to make precise predictions based on data patterns, the integration of causal inference makes these complex models interpretable. The aim is to uncover genuine cause-and-effect relationships. This is particularly valuable in active decision-making processes where different courses of action need to be compared and their impacts assessed. What is particularly exciting is the journey from theory to application: implementing these methods in practice is a highly motivating process. My colleagues and I are working on making the theoretical findings usable in practice through freely available software. A key result of this work is the open-source software package DoubleML, which allows the methods to be applied directly.

Who or what will you remember most fondly from your time at the Business School?

Above all, the close and trusting collaboration with my colleagues at the Institute of Mathematics and Statistics. The joint research projects and the time spent teaching were a formative experience for me.

Which of the School’s core values do you identify with most, and why?

I identify strongly with ‘Impact’. In my research, it is important to me to generate real added value for society and the economy through innovative, methodologically sound insights.

What are you most looking forward to in your new role in Kiel?

The classic answer: meeting my new colleagues and the chance to bring fresh ideas to my research and teaching.

We wish you all the best in your new role at the University of Kiel and look forward to staying in touch with you as an alumnus.

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