Natural Language Processing
About Us
Artificial intelligence, or AI, is increasingly being integrated into our everyday lives. They are in our smartphones (e.g. Siri), facial recognition system in Melbourne Airport, automatic captions on YouTube, and translations on Facebook, just to name a few examples. But how can we make AI truly understand human language? This is an important question, because language is uniquely human — it defines us and our intelligence. Through developing AI that understands language, our research marches one step closer to unlocking the mysteries of our language faculty.
People
Academic Staff
- Tim BaldwinProfessor
Google Scholar tbaldwin@unimelb.edu.au - Trevor CohnProfessor
Google Scholartrevor.cohn@unimelb.edu.au - Eduard Hovy Executive Director
Melbourne Connect
Google Scholareduard.hovy@unimelb.edu.au
- Jey Han Lau Lecturer
Google Scholarjeyhan.lau@unimelb.edu.au - Lea Frermann Lecturer
Google Scholarlea.frermann@unimelb.edu.au - Daniel Beck Lecturer
Google Scholar beck.d@unimelb.edu.au
Research Staff
- Yuan LiResearch Fellow
Google Scholar yuan.li1@unimelb.edu.au - Aili ShenResearch Fellow
Google Scholaraili.shen@unimelb.edu.au - Joseph WestResearch Fellow
Google Scholar
joseph.west@unimelb.edu.au
Honorary Staff
- Karin VerspoorProfessor
Google Scholar - Meladel MisticaResearch Data Specialist
Google Scholar - Simon Šuster
Research Fellow
Google Scholar
NLP Graduate Researchers
Given name | Family name | Profile | Thesis Title |
---|---|---|---|
Uri | Berger | Profile | Interactive multimodal language acquisition |
Shraey | Bhatia | Profile | TBC |
Jiyu | Chen | Profile | Automatic biological data curation based on language understanding and network analysis |
Sayantan | Dasgupta | Profile | TBC |
Biaoyan | Fang | Profile | Anaphora resolution in biochemical text |
Yilin | Geng | Profile | Cross-lingual Representations in Interpretable Language Models |
Xudong | Han | Profile | Gender bias detection and debiasing in models of human language |
Sukai | Huang | Profile | Texted based reinforcement learning agent |
Fan | Jiang | Profile | Retriever-augmented Approaches for Natural Language Processing |
Anirudh | Joshi | Profile | TBC |
Fajri | Koto | Profile | Neural Language Model for Abstractive Text Summarisation |
Kemal | Kurniawan | Profile | TBC |
Haonan | Li | Profile | Geospatial Information with Natural Language Processing |
Miao | Li | Profile | Neural Multi-document Modeling and Abstractive Summarization |
Zheng Wei | Lim | Profile | Cross-lingual Psycholinguistics with NLP methods |
Chunhua | Liu | Profile | Word Association Understanding |
Yulia | Otmakhova | Profile | Multi-document summarization supporting clinical evidence review |
Viktoria | Schram | Profile | Calibration of Performance Prediction in Low-Resource Settings |
Hung Thinh | Truong | Profile | Evidence extraction from the clinical trials literature |
Gisela | Vallejo | Profile | A Fair Plan Towards Mitigating Bias and Misinformation |
Takashi | Wada | Profile | Multilinguality and acceptability in language |
Dalin | Wang | Profile | Image captioning with conditional-GAN |
Jun | Wang | Profile | Adversarial machine learning for machine translation |
Yuxia | Wang | Profile | Clinical text mining and analysis |
Zhuohan | Xie | Profile | Hierarchically structured neural narrative generation |
Rui | Profile | TBC | |
Aotao (John) | Xu | Profile | A computational analysis of conceptual combination through time |
Jinrui | Yang | Profile | Fairness and Bias in Natural Language Processing |
Rongxin | Zhu | Profile | Automatic summarization for multi-party conversation |
Affiliated Graduate Researchers
- Rena Gao (Linguistics)
- Sheilla Njoto (CAIDE)
- Katie Warburton (Science/Psychology)
Research & Publications
From medical technologies to machine translation to misinformation analysis, our group tackles a diverse range of natural language processing problems in different domains and applications, and is ranked one of the top groups internationally in the field.