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.
- If your query is related PhD supervision, it would help to: (1) have a look over my publications to identify areas of overlapping interests; and (2) send a thoughtful research proposal to suggest potential projects. As a student I don’t expect that you have a perfect understanding of the gaps in the field and can identify research questions that fit the scope of a PhD, but the proposal would serve to kickstart a discussion about potential project ideas.
- If your query is about internship, please note that I do not take interns (and so any queries of this nature would not receive a response).
My art+science chatbot project is now being exhibited at NGV Australia (Fed Square)! More information in this article (first project).
3 papers accepted for ACL2022! One Country, 700+ languages, The Patient Is More Dead Than Alive, and An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation.
Our work on understanding mass influence activities online is covered by Guardian.
- Our paper on learning cross-lingual embeddings for low resource languages won the Best Paper Award for MRL 2021!
- Talked about AI and creativity on the radio show PassW0rd (starts at around the 43 minute mark).
- Our IEEE Spectrum article “The AI Poet” is up.
- I’m presenting a talk on “Creativity, Machine and Poetry” at a public forum on language [video].
- Our Shakespearean sonnet generator was covered by New Scientist, Times UK, Daily Mail, and others. More information can be found here.