Emiel Krahmer

Emiel Krahmer is a Professor in the Department of Communication and Cognition at Tilburg University's School of Humanities in the Netherlands. With over 368 publications and more than 7,000 citations, he is a leading researcher in Natural Language Generation (NLG) and Computational Linguistics. His work spans multiple subfields including Referring Expression Generation, Data-to-Text systems, human evaluation methodologies, and more recently, the application of Large Language Models in therapeutic contexts.

Professor Krahmer's research interests focus on the computational aspects of language generation, with particular emphasis on how machines can produce human-like referring expressions, generate text from structured data, and evaluate the quality of automatically generated language. His work combines theoretical linguistics with practical applications, bridging the gap between computational models and human language production. He has made significant contributions to understanding the psychological aspects of language generation and how these can inform computational models.

His recent publications demonstrate a clear evolution in his research trajectory, moving from foundational work in referring expression generation to exploring the capabilities of modern Large Language Models in specialized contexts like motivational interviewing. The analysis of his 15 most recent articles reveals a strong focus on reproducibility in human evaluation studies, the application of NLG techniques in healthcare contexts, and the development of robust evaluation frameworks for NLG systems. His work increasingly intersects with clinical psychology and therapeutic applications, showing how language generation technology can be adapted for sensitive communication contexts.

Professor Krahmer has been instrumental in organizing key events in the NLG community, including serving as co-editor for the Proceedings of the First Workshop on Natural Language Generation in Healthcare (2021). His work on human evaluation best practices has helped establish standards in the field, while his research on reproducibility addresses critical methodological challenges in NLP research.

His collaborations span multiple institutions and disciplines, reflecting the interdisciplinary nature of his work. He has mentored numerous researchers who have gone on to make their own contributions in computational linguistics, as evidenced by his extensive co-authorship network. While specific lab affiliations aren't detailed in the provided information, his work is clearly embedded within Tilburg University's research ecosystem focused on language technology and human communication.