Dr. Tobias R. Rebholz

As an interdisciplinary scholar and open-science enthusiast, I address research questions about human and AI behavior using methods from statistics, econometrics, machine learning, and behavioral science. This includes experimental research on social cognition, human-computer interaction, and machine behavior.

I am currently a DFG-funded Walter Benjamin Fellow and visiting research scholar in the Management and Organizations Area at Duke University's Fuqua School of Business. Previously, I was a research associate in the Social Cognition and Decision Sciences group in the Department of Psychology at the University of Tübingen, Germany.

I earned my PhD in Psychology in 2023 from the DFG-funded Research Training Group Statistical Modeling in Psychology (SMiP)—a transregional collaboration involving the Universities of Mannheim, Freiburg, Heidelberg, Landau, and Tübingen. My academic foundation lies in business studies and economics, with a BSc in 2017 and an MSc in 2020, both from the University of Konstanz, Germany.

I serve on the editorial board of the Journal of Behavioral Decision Making, as a recommender (associate editor) at Peer Community In: Registered Reports, and as a website editor and associated member of the executive board of the European Association for Decision Making.

Given the name I was dealt, studying what tends “to bias” estimates and behavior feels like nominative determinism—or, at times, an occupational hazard. In other words, my research focuses on investigating biases both in a statistical sense (i.e., improving the estimation of effects and phenomena) as well as from a psychological perspective—specifically, in people’s judgment and decision-making (JDM).

A central theme in my current work is quantifying the influence of qualitative information—especially text generated by large language models (LLMs) such as OpenAI’s ChatGPT or Google’s Gemini—on how humans form judgments, make choices, and update their beliefs. More broadly, I develop and apply advanced statistical and machine learning methods to understand how ecological constraints shape information sampling and utilization.

My research has secured over 150,000 EUR in competitive funding and has been published in prestigious outlets, including Psychological Inquiry, Judgment and Decision Making, the Journal of Behavioral Decision Making, and the Journal of Experimental Psychology: Applied.

The following articles, some of which are award-winning publications in the respective outlets, are a representative selection of my work on behavioral science and quantitative methods (see publications, for a full list of articles, incl. software/data, preprints, and manuscripts):

My teaching spans substantive research seminars on broadly defined topics of human and AI decision-making in various contexts. I also teach courses on the methodology of applied machine learning, statistical programming, and experimental data analytics.

Beyond academia, I am trained as a professional chef (see culinary corner for details). I was in one of the first cohorts of the double-degree program LIZE-Koch (Gesellenbrief + Abitur), which has since become an established program at my former German high school. I worked as a sous-chef at the Restaurant Donauperle for many years and as a restaurant critic for Seezunge, a regional dining guide around Lake Constance in Germany, Austria, and Switzerland. Although I no longer cook professionally, I continue to volunteer in various culinary roles—for example, cooking for youth and community programs.

On this website, you can find my vita, an overview of my main research projects, as well as lists of publications and contributions to conferences. If you have any questions or would like to connect, feel free to reach out at tr.rebholz@gmail.com.