I am a post-doctoral researcher in statistical machine translation and VENI laureate since September 2016. I work with a team of six PhD students led by Christof Monz, and I co-supervise three: Marlies van der Wees, Ke Tran and Marzieh Fadaee. Currently, the main goal of my work is to improve SMT into morphologically rich languages, for instance using class-based language models or neural translation models.

Interested in my work ? See my Research page.


  • [Oct 2016]   I'm coming back to work (very gradually) after an extraordinary summer spent on maternity leave!
  • [Sep 2016]   Paper accepted at COLING 2016: "Measuring the Effect of Conversational Aspects on Machine Translation Quality", M. van der Wees, A. Bisazza and C. Monz.
  • [Jul 2016]   I won a VENI grant (250K personal grant from the Dutch research funding agency) to fund my project "Connecting the Dots: Minimal Structure Modeling for Machine Translation"!
  • [Jul 2016]   Paper accepted at EMNLP 2016: "Neural versus Phrase-Based Machine Translation Quality: a Case Study", L. Bentivogli, A. Bisazza, M. Cettolo and M. Federico.
  • [Jun 2016]   My survey finally appears on Computational Linguistics: "A Survey of Word Reordering in Statistical Machine Translation: Computational Models and Language Phenomena", A.Bisazza and M. Federico.
  • [Mar 2016]   Paper accepted at NAACL 2016: "Recurrent Memory Networks for Language Modeling", K. Tran, A. Bisazza and C. Monz.
  • [Feb 2016]   We got a Google Research Award to partially fund my research on decoding-time generation for SMT into morphologically rich languages!

Research interests

(for more details see my Research page)

Machine Translation:

  • Translation from/into morphologically rich languages
  • Neural language and translation modeling
  • Enhancing statistical models with linguistically motivated techniques
  • Word reordering between distant languages
  • Domain adaptation

Speech Recognition:

  • Linguistic pre-processing and language modeling methods for morphologically rich languages


  • Italian, English and French
  • ... but more interestingly: Turkish (advanced speaking and reading) and Arabic (mostly reading).