I am a first year PhD student with the UK Research & Innovation Centre for Doctoral Training in Natural Language Processing at the University of Edinburgh. Previously, I graduated from the master in AI from the University of Amsterdam.

I am interested in conducting AI research by taking human intelligence as a point of reference and adapting computational models such as to reflect human inductive biases. The facet of human intelligence that intrigues me most is natural language. Within the field of NLP my main research interest is the evaluation of and improvement of techniques for compositional generalisation in neural models of language. Previously, I worked on multitask learning for metaphor detection.

Selected Publications

  • Compositionality Decomposed: How do Neural Networks Generalise?
    Dieuwke Hupkes, Verna Dankers, Mathijs Mul, and Elia Bruni
    In Journal of Artificial Intelligence Research, 67, pages 757-795 [paper] [extended abstract (IJCAI)]
  • Modelling the interplay of metaphor and emotion through multitask learning
    Verna Dankers, Marek Rei, Martha Lewis, and Ekaterina Shutova
    In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 2218-2229 [paper]
  • Modelling word associations with word embeddings for a guesser agent in the Taboo city challenge competition
    Verna Dankers, Aysenur Bilgin, and Raquel Fernández. In The 6th ESSENCE Workshop: the Taboo city challenge competition @ IJCAI-2017 [paper]