Tanya Braun

Tanya Braun is a Junior Professor in the Institute of Computer Science at the University of Münster, Department of Mathematics and Computer Science. She leads the Data Science research group, focusing on statistical-relational AI, human-aware AI, and text understanding. Her work bridges formal AI methods with real-world applications in healthcare, digital humanities, and public sector systems.

Education:

• Bachelor's and Master's in Computational Informatics, Hamburg University of Technology
• Doctorate in Computer Science, University of Lübeck (2020), thesis: 'Rescued from a Sea of Queries - Exact Inference in Probabilistic Relational Models'

Her research centers on probabilistic inference in relational domains, with a focus on lifted inference techniques that exploit symmetries to scale reasoning. She investigates human-aware AI, particularly how AI systems can reconcile learned models with human expectations to improve explainability and trust. Her work on text understanding addresses challenges in data-scarce settings such as digital humanities, where traditional large language models fail. She has developed methods for identifying and enriching subjective content descriptions, topic modeling in specialized domains, and feedback-driven model improvement.

The 15 most recent publications highlight a strong trajectory in lifted inference, model compression, privacy-preserving AI, and explainability. Her work integrates formal AI foundations with practical concerns in high-stakes domains like healthcare. She frequently publishes in top venues such as AAAI, IJCAI, ECAI, and Artificial Intelligence, often in collaboration with Ralf Möller, Marcel Gehrke, and Jan Speller.

Scientific Awards:

• No specific awards listed in the provided text.

Tanya Braun actively advises students and leads the HAPPI project, which focuses on human-AI model reconciliation using lifted probabilistic inference. She has supervised multiple theses and mentored researchers including Jan Speller (PostDoc), Nazlı Nur Karabulut, and Sagad Hamid. She has secured funding from the Ministry of Culture and Science of North Rhine-Westphalia for her research. She is deeply involved in academic service: serving as program co-chair for KI 2025, guest-editing special issues in journals like Künstliche Intelligenz and Annals of Mathematics and Artificial Intelligence, and organizing major conferences including ICCS and KR.

Labs and Teams: She leads the Data Science Group at the University of Münster, which conducts research in AI, probabilistic modeling, and data science. The group is actively involved in teaching and mentoring students in advanced AI topics.