Welcome to my website! 👋 I am a PhD student at the Computational Linguistics Group of the University of Groningen and member of the InDeep consortium, working on user-centric interpretability for neural machine translation. I am also the main developer of the Inseq library. My supervisors are Arianna Bisazza, Malvina Nissim and Grzegorz Chrupała.
Previously, I was a research intern at Amazon Translate, a research scientist at Aindo, a student in the Data Science MSc at the University of Trieste and a co-founder of the AI Student Society. My master’s thesis with the ItaliaNLP Lab discussed the study of linguistic complexity using gaze recordings and neural language models.
My research currently focuses on interpretability for NLP models, in particular to the benefit of end-users and by leveraging human behavioral signals. I am also passionate about social applications of machine learning, causality topics, and open source collaboration.
Our paper DivEMT: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages is accepted at EMNLP 2022! Code, 🤗 Dataset and demo are available.
An open-source library to democratize access to model interpretability for sequence generation models
The first CLIP model pretrained on the Italian language.
A semantic browser for SARS-CoV-2 and COVID-19 powered by neural language models.
Generating letters with a neural language model in the style of Italo Svevo, a famous italian writer of the 20th century.