My field of research is in Natural Language Processing (NLP) — a sub-field of Artificial Intelligence — and the goal of NLP is to develop computational models to understand human languages. There are a host of NLP applications that are commonly used in our everyday lives: machine translation (e.g. Google Translate) and chatbot (e.g. Siri) are two examples. My research focuses on building computational models in an unsupervised or semi-supervised setting, i.e. a learning scenario where the supervision signal for model training is not available or scarce, and is characterised by a diverse flavour of applications, e.g. topic models, lexical semantics, text generation and misinformation detection. Some of my research has a broader community interest beyond academia — e.g. my work in text generation and influence operations has been covered by science magazines (New Scientist) and mainstream news media (Guardian and BBC).

Prior to joining the University of Melbourne, I spent over 3.5 years as an industry scientist at IBM Research, developing solutions for clients in application domains from education to government.

Affiliations: The University of Melbourne’s NLP Group and Information and Influence Hub.


Prospective Students

  • I am not recruiting PhD students at the moment (though this may change in the future).
  • Unfortunately I also do not take interns, as such do not expect a response to these enquiries.