Julian Rosenberger

Julian Rosenberger

PhD Researcher in Human-AI Interaction
University of Regensburg & TU Dresden
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About

I am a PhD researcher at the University of Regensburg and TU Dresden, supervised by Mathias Kraus and Patrick Zschech.

My research interests are in interpretable machine learning, human-AI interaction, and explainable AI. I use behavioral experiments to study how people understand and work with transparent ML systems, and whether common assumptions about interpretability actually hold up in practice. I'm currently interested in conversational approaches to explainability, how personalizing models to individual users affects trust and decision-making, and how different explanation scopes (global vs. local) shape users' mental models. I also work on new visualization approaches for XAI.

Before my PhD, I studied International Information Systems at FAU Erlangen-Nuremberg and worked in product design at Allianz Global Digital Factory. Feel free to reach out at hi@julianrosenberger.com.

Selected Publications

Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users
J. Rosenberger, P. Schröppel, S. Kruschel, M. Kraus, P. Zschech, and M. Förster
European Conference on Information Systems (ECIS), 2025
CareerBERT: Matching Resumes to ESCO Jobs in a Shared Embedding Space for Generic Job Recommendations
J. Rosenberger, L. Wolfrum, S. Weinzierl, M. Kraus, and P. Zschech
Expert Systems with Applications, 2025
Understanding Data-Sharing with AI Systems: The Roles of Transparency, Trust, and the Processing Entity
J. Rosenberger, S. Kuhlemann, M. Kraus, P. Zschech, and V. Tiefenbeck
Pacific Asia Journal of the Association for Information Systems (PAJAIS), in press

Full list on Google Scholar.

Experience

Education