Kevin Stowe


  • Februrary 2023 In "Lessons Learned from a Citizen Science Project for Natural Language Processing", our group at UKP explores citizen science data collection for NLP: upcoming at EACL 2023!
  • December 2022: Our lab at ETS has been working on automatically generating language learning items, specifically by adding control to better customize the outputs. See Controlled Language Generation for Language Learning Items at the Industry Track of EMNLP 2022, coming soon!
  • June 2022: We built a new dataset, IMPLI, of paired literal and figurative expressions, designed for NLI and generation tasks. Check it out at ACL 2022!


  • I'm currently an Associate Research Scientist at ETS, working with the Automatic Content Generation team to build better education and testing tools!
  • Previously, I worked as a postdoctoral researcher with Prof. Dr. Iryna Gurevych at the UKP Lab in Darmstadt, Germany.
  • Before that I was a research assistant at the CLEAR Lab at the University of Colorado under Prof. Martha Palmer while pursuing my PhD. I also worked for Project EPIC under Prof. Leysia Palen.


  • I completed my PhD. from the University of Colorado in August, 2019.
  • Masters in Linguistics from Indiana University, Dec 2010.
  • BA in Linguistics from Michigan State University, May 2009


  • Language Generation: Using language models (including but not limited to GPT) to generate text is fun, and getting better: how can we control the outputs to ensure they match our requirements, while mitigating bias and hallucination?
  • Computational creativity: How do machines process creative language? Can we detect it? Can we generate it? Metaphors, metonymy, sarcasm, humor, and more all pose significant challenges even to state-of-the-art systems.
  • Crisis Informatics: How do we best make of use of the massive amount of data created during crisis events (including natural disasters like hurricanes, terrorist events/wars, and pandemics like COVID-19)? Social media can help, but applying NLP can be difficult, and we deal with issues of data collection and annotation, machine learning, and ethical issues.
  • NLP for Social Good: Relatedly, how can we leverage the vast amount of power AI has to improve peoples lives in concrete ways? How do we deal with ethical issues, problems of inclusivity, and systematic bias in data, systems, and researchers?
  • Language: My background is originally in linguistics - I'm always interested in studying linguistic problems, particularly in semantics and pragmatics. Other areas of interest include construction grammar, frame semantics, and creative language.