CV

CV

  • since August 2019: SNSF Professor at University of Zurich.
  • since August 2017: Lecturer (Assistant Professor) at University of Edinburgh.
  • 2017‒2019: (part-time) researcher at University of Zurich. Projects:
  • 2015‒2017: research associate at University of Edinburgh. Projects:
    • research collaborations with Samsung (2015-2016; 2017)
    • TraMOOC (2015-)
    • QT21 (2015-)
    • SUMMA (2016-2017)
  • 2015: external lecturer at University of Zurich: "Advanced Topics in Machine Translation"
  • 2013‒2015: SNSF mobility fellowship at University of Edinburgh: improving fluency with syntax-based statistical machine translation.
  • 2012‒2014: Cooperation project with Finnova in Statistical Machine Translation.
  • 2010‒2013: PhD in Computational Linguistics. Researcher in project Domain-specific Statistical Machine Translation
  • September‒December 2012: Research stay at Laboratoire d'Informatique de l'Université du Maine
  • 2004‒2010: Master in English Language and Literature, Computational Linguistics and Educational Science at University of Zurich
  • 2006‒2007: Erasmus study year at Lancaster University

Invited talks

  • 18.10.2021. On Exposure Bias, Hallucination and Domain Shift in Neural Machine Translation. Unbabel.
  • 7.7.2021. How Contextual is Neural Machine Translation? TRITON conference.
  • 29.6.2021. Lessons from Multilingual Machine Translation. Huawei CRI Vision Forum Virtual Workshop on AI & ML.
  • 29.1.2021. Lessons from Multilingual Machine Translation. University of Colorado at Boulder, USA.
  • 2.12.2020. Towards Reliable Zero-Shot Machine Translation. Uppsala University, Sweden.
  • 18.5.2020. How Contextual is Neural Machine Translation?. GeCKo symposium.
  • 10.2.2020. Document-level Machine Translation: Recent Progress and The Crux of Evaluation. University of Stuttgart, DE.
  • 14.1.2020. Document-level Machine Translation: Recent Progress and The Crux of Evaluation. Tianjin University, ZH.
  • 11.10.2019. What Do Transformers Learn in NLP? Recent Insights from Model Analysis. EurNLP, London, UK.
  • 25.4.2019. Document-level Machine Translation: Recent Progress and The Crux of Evaluation. NYU Centre of Data Science, New York, USA.
  • 15.2.2019. Neural Machine Translation. What’s linguistics got to do with it?. SOIL-Tech 2019, New Delhi, India (remotely)
  • 27.10.2018. Why the Time Is Ripe for Document-Level Machine Translation. Tianjin University, ZH.
  • 25.10.2018. Revisiting Challenges in Neural Machine Translation. The 14th China Workshop on Machine Translation. Wuyishan, ZH
  • 23.10.2018. Why the Time Is Ripe for Document-Level Machine Translation. The 1st International Workshop on Discourse Processing. Guangzhou, ZH.
  • 20.7.2018. Why the Time Is Ripe for Discourse in Machine Translation. The 2nd Workshop on Neural Machine Translation and Generation, Melbourne, AU.
  • 3.11.2017. Neural Machine Translation: what's linguistics got to do with it? Tartu University, Estonia.
  • 1.11.2017. Neural Machine Translation: what's linguistics got to do with it? Second Finnish Workshop on Machine Translation, Helsinki, Finland.
  • 30.8.2017. Neural Machine Translation: what's linguistics got to do with it? Text Speech & Dialogue 2017, Prague, Czech Republic.
  • 14.3.2017. Neural Machine Translation. Booking.com, Amsterdam, NL.
  • 24.11.2016. Neural Machine Translation: Breaking the Performance Plateau. LIMSI, Paris, FR.
  • 28.10.2016. Neural Machine Translation: Breaking the Performance Plateau. AMTA 2016, Austin, Texas, USA.
  • 4.7.2016. Neural Machine Translation: Breaking the Performance Plateau. META-FORUM 2016, Lisbon, PT.
  • 24.6.2016. Recent Advances in Neural Machine Translation. Apple, Cupertino, USA.
  • 23.6.2016. Recent Advances in Neural Machine Translation. Google, Mountain View, USA.
  • 21.1.2016. Recent Advances in Neural Machine Translation. Facebook AI Research, Paris, FR.
  • 21.12.2015. Syntax-based Machine Translation. Universität Konstanz, DE.
  • 17.9.2013. A Multi-Domain Translation Model Framework for Statistical Machine Translation. Xerox Center Europe, Grenoble, F.
  • 31.8.2012. Promoting Flexible Translations in Statistical Machine Translation. University of Tilburg, NL.
  • 29.8.2012. Steps towards a quickly adaptable multi-domain SMT system. Radboud University Nijmegen, NL.
  • 14.3.2012. Quick and Painless Domain Adaptation for Statistical Machine Translation. Université du Maine, Le Mans, F.
  • 26.6.2010. MT-based Sentence Alignment for OCR-generated Parallel Texts. Tacos 2010, Zurich, CH.

Tutorials