Isabelle Augenstein is a Professor at the University of Copenhagen's Department of Computer Science, where she leads the Copenhagen Natural Language Understanding (CopeNLU) research group and the Natural Language Processing section. She became Denmark's youngest female full professor in 2022 and co-leads the Danish Pioneer Centre for Artificial Intelligence's Speech and Language collaboratory. ERC Starting Grant recipient DFF Sapere Aude Research Leader fellow Karen Spärck Jones Award winner Hartmann Diploma Prize recipient Her research focuses on fair and accountable NLP systems, with specific emphasis on explainability, factuality, bias detection, and social NLP. She investigates cultural biases in language models, develops frameworks for explainable fact checking, and explores uncertainty estimation in NLP systems. Recent publications demonstrate expertise in: Mechanistic analysis of cultural bias representations Context utilization techniques for LLMs Explainability metrics and attribution methods Cross-domain label adaptation Retrieval-augmented generation Fact checking uncertainty quantification Major scientific contributions include: Numerous EMNLP and ACL publications Foundational work on stance detection Development of fact checking benchmarks Multilingual model analysis AI ethics frameworks She supervises a team of researchers working on explainable AI and fact checking systems, with current projects including the ExplainYourself ERC-funded initiative on explainable fact checking. Her group recently presented multiple papers at EMNLP 2025 on topics spanning explainable AI and social NLP.
