- I delivered my probationary lecture for promotion to Docent rank at Uppsala University on 14 November 2019. The topic was Gender Bias as an Issue in Natural Language Processing. Now waiting for the faculty board to make a decision.
- Two more talks on Discourse Phenomena in Machine Translations:
- 19 November 2019: SMART-Select Workshop on Document-Level MT Evaluation, Luxembourg.
- 22 November 2019: Saarland University, Department of Language Science and Technology.
- I’m one of the organisers of the following two workshops in 2020:
- Second Workshop on Gender Bias in Natural Language Processing (GeBNLP 2020) at COLING 2020 in Barcelona, 13 or 14 September 2020.
- First Workshop on Computational Approaches to Discourse (CAD 2020) at EMNLP 2020 in Punta Cana, 11 or 12 November 2020.
I’m a Researcher in Computational Linguistics at Uppsala University. From summer 2019 until the end of 2020, I’m working at the University of Edinburgh, and during some of that time, I’m also a Senior Researcher at the School of Informatics at the University of Edinburgh. Before I came to Uppsala, I was in the machine translation group at Fondazione Bruno Kessler in Trento.
I hold a PhD in Computational Linguistics from Uppsala University. My PhD thesis was on Discourse in Statistical Machine Translation and received the Best Thesis Award of the European Association for Machine Translation in 2015. My supervisors were Joakim Nivre, Jörg Tiedemann and Marcello Federico. I also have an MA in Nordic Philology from the University of Basel.
I work in computational linguistics, and my research is at the intersection of statistical natural language processing, machine translation, translation studies and text linguistics. My goal is to study high-level problems in translation using methods from statistical NLP and machine translation and use those insights to enable progress in MT and multilingual NLP.
I’m particularly interested in how referring expressions such as pronouns (like she, it, they or this) and lexical noun phrases (like a cat, the house, scrambled eggs or my research) are used across languages, how human translators treat them, what machine translation systems should do with them and how we can use multilingual data to help us interpret them automatically.
Here are some of the angles from which I’ve approached these problems in the last few years:
- Discourse-level MT and its evaluation (1, 2, 3)
- Automatic discovery of discourse-related language contrasts in human-translated parallel corpora (4, 5)
- Cross-lingual studies of the generation and interpretation of referring expressions with human subjects (6, 7)
- Coreference annotation of multilingual corpora (8, 9)
- Neural language modelling (10) and cross-lingual pronoun prediction (11, 12)
In 2019, I’m one of the organisers of the 1st Workshop on Gender Bias in Natural Language Processing (GeBNLP) at ACL in Florence and of the 4th Workshop on Discourse in MT (DiscoMT) at EMNLP in Hong Kong.