Ildikó Pilán received her PhD in Natural Language Processing at the Swedish Language Bank, at the University of Gothenburg in 2018. Her research topics so far have included intelligent computer-assisted language learning, linguistic linked open data, computational lexicography and algorithmic bias.
Previous Experience
- Oct 2018 - Jan 2019, CTO / Research Scientist, Develop Diverse. Research and development on detection and replacement of stereotypical language using natural language methods. <https://www.developdiverse.com/>.
Journal
- Pilán, Ildikó. , Volodina, Elena. & Borin, Lars. (2016). Candidate sentence selection for language learning exercises: from a comprehensive framework to an empirical evaluation. Traitement Automatique des Langues (TAL), Special issue on NLP for learning and teaching. 57. 67 - 91.
Conference Paper
- Pilán, Ildikó. , Volodina, Elena. & Zesch, Torsten. (2016). Predicting proficiency levels in learner writings by transferring a linguistic complexity model from expert-written coursebooks. 26th International Conference on Computational Linguistics (COLING). (pp. 2101 - 2110). Osaka. Japan: .
Book
- Pilán, Ildikó. (17 May 2018). Automatic proficiency level prediction for Intelligent Computer-Assisted Language Learning. Gothenburg: University of Gothenburg. 978-91-87850-68-4.
