Felix Süttmann

Felix Süttmann is an applied statistician affiliated with Georg-August-University Göttingen and works at the German Institute for Economic Research (DIW Berlin) since 2022. He focuses on survey methodology, including nonresponse modeling, mixed-mode effects, and complex weighting, while also engaging with Bayesian statistics and machine learning applications.

• Doctoral candidate at Berlin Graduate School of Social Sciences
• Previously worked as a sampling statistician at the International Association for the Evaluation of Educational Achievement (IEA) for TALIS

Research interests span natural language processing, Bayesian modeling, and sustainability, with a strong emphasis on methodological rigor in survey research and econometrics. His work at DIW involves improving nonresponse adjustment factors using ML tools and developing stand-alone weights for refugee samples.

Recent publications address sampling techniques in SOEP, nonresponse correction, and weighting methodologies for migration studies, alongside his 2020 work on deep learning for NLP. His methodological contributions include copula-based Bayesian hierarchical models for sample selection.

Lectures and presentations cover topics like nationwide household sampling, survey mode preferences, and record linkage weighting adjustments at conferences such as the European Survey Research Association (ESRA) and the Society for Longitudinal and Life Course Studies (SLLS).