---
title: "Australia — research institutions, scientists and papers"
description: "Australia: 15 institutions with papers in our library in 5 agglomerations, 53 people with a page, 116 works, 172,075 citations."
canonical: "https://research.elamur.ai/free/en/countries/australia/"
---
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# Australia

Country 15 institutions in 5 agglomerations · [all countries](https://md.research.elamur.ai/free/en/countries/)

[**15** institutions with a page](https://md.research.elamur.ai/free/en/countries/australia/#institutions) · [**5** agglomerations](https://md.research.elamur.ai/free/en/countries/australia/#agglomerations) · [**53** people with a page](https://md.research.elamur.ai/free/en/countries/australia/#authors) · [**116** works in our library](https://md.research.elamur.ai/free/en/countries/australia/#works) · [**172,075** citations of their works](https://md.research.elamur.ai/free/en/countries/australia/#works)

## About

### Profile

This overview covers Australia as it appears in the library: the universities, laboratories and public research bodies based in the country whose scientists have written more than one of the papers collected on this site. It does not survey Australian science as a whole. It is a map of the Australian organisations that recur among the works here. The full list is on the [Australia country page](https://md.research.elamur.ai/free/en/orgs/country/au/), and the library's [directory of institutions of all kinds](https://md.research.elamur.ai/free/en/orgs/) puts these Australian entries beside organisations from other countries.

Institutions are ordered by the cited work their researchers produced while affiliated with them, not by size or age. On this site, Australian research is concentrated in a small number of cities. Most of the organisations are universities. The rest are research institutes and one government body. Their contributions differ a great deal: some appear through a large and varied set of papers, while others appear through a few works that have drawn heavy citation.

### Where the research happens

Sydney and Melbourne account for most of the Australian institutions represented. Sydney has the largest cluster. It includes [The University of Sydney](https://md.research.elamur.ai/free/en/universities/the-university-of-sydney/), the [University of Technology Sydney](https://md.research.elamur.ai/free/en/universities/university-of-technology-sydney/), [Macquarie University](https://md.research.elamur.ai/free/en/universities/macquarie-university/) and [UNSW Sydney](https://md.research.elamur.ai/free/en/universities/unsw-sydney/), along with the research institute [Data61](https://md.research.elamur.ai/free/en/labs/data61/). Melbourne follows, with [The University of Melbourne](https://md.research.elamur.ai/free/en/universities/the-university-of-melbourne/), [Monash University](https://md.research.elamur.ai/free/en/universities/monash-university/), [RMIT University](https://md.research.elamur.ai/free/en/universities/rmit-university/) and the industrial laboratory [IBM Research - Australia](https://md.research.elamur.ai/free/en/labs/ibm-research-australia/).

The national capital, Canberra, has two entries. One is the [Australian National University](https://md.research.elamur.ai/free/en/universities/australian-national-university/). The other is the [Commonwealth Scientific and Industrial Research Organisation](https://md.research.elamur.ai/free/en/government/commonwealth-scientific-and-industrial-research-organisation/), the only government body in the Australian list. Brisbane has [Griffith University](https://md.research.elamur.ai/free/en/universities/griffith-university/) and [Queensland University of Technology](https://md.research.elamur.ai/free/en/universities/queensland-university-of-technology/). Perth has [The University of Western Australia](https://md.research.elamur.ai/free/en/universities/the-university-of-western-australia/), and Darwin has [Charles Darwin University](https://md.research.elamur.ai/free/en/universities/charles-darwin-university/).

The south-eastern cities therefore carry most of the weight. Canberra, Brisbane, Perth and Darwin each add a smaller number of contributing organisations. Among the works here, the country's research is spread across several institutions in a few urban centres, with no single organisation dominating.

### The universities

Universities make up most of the Australian list, and the most strongly represented institutions are all universities.

The University of Melbourne is ranked first. It also has the broadest body of work of any Australian institution on the site, contributing more papers than any other organisation in the country. Its citations are spread across that larger set of works, which suggests sustained activity in many projects rather than reliance on one or two highly cited outputs.

Monash University, also in Melbourne, takes second place. Monash contributes fewer works than either Melbourne or Sydney, yet its works have attracted a very large share of citations. This points to a set of papers with strong individual influence.

The University of Sydney comes third. In total citations it has the largest cited output of any Australian institution on the site, from a body of work bigger than Monash's but smaller than Melbourne's. It does not rank first because the ordering weighs the cited work attributed to scientists' time at the institution, not raw totals alone.

The University of Technology Sydney is the clearest case of concentrated influence. It appears with only a handful of works, but these have drawn a very large number of citations. That places it fourth, ahead of institutions with much larger bodies of work on the site. Its position on the list rests on a few heavily cited papers.

Macquarie University shows the opposite pattern. It has more works on the site than several institutions ranked near it, but they are cited more modestly on average. The Australian National University follows with a smaller set of works and a comparable level of citation. Together, Macquarie and the Australian National University form a middle group: neither has the large output of Melbourne nor the citation concentration of the University of Technology Sydney.

Further down, Griffith University is represented by only a couple of works, which have nonetheless been cited fairly widely. UNSW Sydney has more works than Griffith but a smaller cited total, so Sydney's larger universities contribute in quite different ways. Queensland University of Technology and The University of Western Australia each appear with a small group of works of similar citation impact. RMIT University has a somewhat larger set of works, which have been cited less often. Charles Darwin University is the final entry, appearing through a pair of works with a more limited citation record.

### Research institutes and the government sector

Several entries are not universities, and they show how applied and industrial research figures in Australia's presence on the site.

Data61, a Sydney research institute, contributes a steady group of works, more than several of the universities listed after it. Their citation level puts it in the middle of the national list.

The Commonwealth Scientific and Industrial Research Organisation, the government body based in Canberra, appears with a small number of works. These have been cited more than those of some universities ranked just above it. Its place in the ordering again shows that position depends on how cited work is credited to researchers' time there, not only on overall citation totals.

IBM Research - Australia, in Melbourne, is the one corporate research laboratory among the Australian entries. It is represented by a pair of works whose citations exceed those of some institutions with larger bodies of work on the site. The library's description of the list allows for companies, but in this list corporate research appears only through this laboratory.

### How the ranking reads

The ordering does not simply follow the number of works or the total citations. The University of Melbourne leads with the largest number of works but not the most citations. The University of Sydney has the largest cited total but is placed third. Lower down, the Commonwealth Scientific and Industrial Research Organisation sits below UNSW Sydney despite more cited work in total, and The University of Western Australia and IBM Research - Australia appear below institutions whose citation totals are smaller.

These differences come from the way the site credits work. Influence is assigned to the time a researcher actually spent at an institution, so an organisation's rank reflects the cited research done there rather than everything its past or present staff have published. A university whose scientists produced much of their most cited work after moving elsewhere may therefore rank lower than its totals suggest. An institution where influential work was done during a researcher's time there may rank higher.

The list also brings out two different ways institutions contribute. Some, led by The University of Melbourne and including Macquarie University, Data61 and RMIT University, appear through relatively many works. Others, especially the University of Technology Sydney, Monash University, Griffith University and IBM Research - Australia, appear mainly through a few works that have been cited heavily. A short list of high-impact papers and a broad body of steady output both lead to a place on the list, but they describe different kinds of research presence.

### Using the Australian list

Each institution has its own page in the library, listing its works, the researchers credited there and the subjects it covers. Readers who want the details of a particular organisation's research can start from the links above. The Australian list is mainly a way into those pages and a summary of how the country's institutions compare with one another.

The picture depends on the collection as it currently stands. It is limited to institutions whose researchers wrote more than one of the papers here, so Australian organisations with a single paper on the site, or none, do not appear. As the library grows, the list and its order may change: new institutions may join, and the balance between the Sydney and Melbourne clusters and the smaller centres may shift. For now, Australian research on the site is concentrated in universities in Sydney and Melbourne. Canberra, Brisbane, Perth and Darwin add further universities, and a research institute, a corporate laboratory and a national government science agency complete the list.

## Where

## Agglomerations (5)

1. [**Sydney**5 institutions*86,752 citations*](https://md.research.elamur.ai/free/en/agglomerations/sydney/)
2. [**Melbourne**4 institutions*74,966 citations*](https://md.research.elamur.ai/free/en/agglomerations/melbourne/)
3. [**Belconnen**2 institutions*5,347 citations*](https://md.research.elamur.ai/free/en/agglomerations/north-canberra-canberra/)
4. [**Brisbane**2 institutions*3,090 citations*](https://md.research.elamur.ai/free/en/agglomerations/brisbane/)
5. [**Perth**1 institution*1,666 citations*](https://md.research.elamur.ai/free/en/agglomerations/perth/)

## Institutions (15)

### 🎓 Universities (12)

**[The University of Sydney](https://md.research.elamur.ai/free/en/universities/the-university-of-sydney/)**University · [Sydney](https://md.research.elamur.ai/free/en/agglomerations/sydney/), Australia*29 works · 67,547 citations*

**[Monash University](https://md.research.elamur.ai/free/en/universities/monash-university/)**University · [Melbourne](https://md.research.elamur.ai/free/en/agglomerations/melbourne/), Australia*23 works · 53,551 citations*

**[The University of Melbourne](https://md.research.elamur.ai/free/en/universities/the-university-of-melbourne/)**University · [Melbourne](https://md.research.elamur.ai/free/en/agglomerations/melbourne/), Australia*47 works · 19,957 citations*

**[University of Technology Sydney](https://md.research.elamur.ai/free/en/universities/university-of-technology-sydney/)**University · [Sydney](https://md.research.elamur.ai/free/en/agglomerations/sydney/), Australia*4 works · 11,827 citations*

**[Macquarie University](https://md.research.elamur.ai/free/en/universities/macquarie-university/)**University · [Sydney](https://md.research.elamur.ai/free/en/agglomerations/sydney/), Australia*12 works · 4,052 citations*

### 🔬 Labs and research institutes (2)

**[Data61](https://md.research.elamur.ai/free/en/labs/data61/)**Research institute · [Sydney](https://md.research.elamur.ai/free/en/agglomerations/sydney/), Australia*9 works · 2,187 citations*

**[IBM Research - Australia](https://md.research.elamur.ai/free/en/labs/ibm-research-australia/)**Research institute · [Melbourne](https://md.research.elamur.ai/free/en/agglomerations/melbourne/), Australia*2 works · 1,005 citations*

### 🏛️ Government research bodies (1)

**[Commonwealth Scientific and Industrial Research Organisation](https://md.research.elamur.ai/free/en/government/commonwealth-scientific-and-industrial-research-organisation/)**Government body · [Canberra](https://md.research.elamur.ai/free/en/agglomerations/north-canberra-canberra/), Australia*4 works · 1,633 citations*

[See all 15 institutions →](https://md.research.elamur.ai/free/en/countries/australia/institutions/)

## People (53)

Authors with a page confirmed at its institutions, the most cited first.

[🧑‍🔬**Shirui Pan** Monash University 2 papers here · 12,835 citations](https://md.research.elamur.ai/free/en/authors/shirui-pan/) · [🧑‍🔬**Timothy Baldwin** The University of Melbourne 26 papers here · 10,796 citations](https://md.research.elamur.ai/free/en/authors/timothy-baldwin/) · [🧑‍🔬**Mark Johnson** Macquarie University 14 papers here · 9,545 citations](https://md.research.elamur.ai/free/en/authors/mark-johnson/) · [🧑‍🔬**Fangyu Liu** Monash University 2 papers here · 6,521 citations](https://md.research.elamur.ai/free/en/authors/fangyu-liu/) · [🧑‍🔬**Tim Miller** The University of Melbourne 2 papers here · 5,491 citations](https://md.research.elamur.ai/free/en/authors/tim-miller/) · [🧑‍🔬**Trevor Cohn** The University of Melbourne 9 papers here · 5,266 citations](https://md.research.elamur.ai/free/en/authors/trevor-cohn/) · [🧑‍🔬**Shervin Malmasi** Macquarie University 10 papers here · 5,046 citations](https://md.research.elamur.ai/free/en/authors/shervin-malmasi/) · [🧑‍🔬**Tianyu Liu** University of Technology Sydney 8 papers here · 3,319 citations](https://md.research.elamur.ai/free/en/authors/tianyu-liu/) · [🧑‍🔬**Dat Quoc Nguyen** The University of Melbourne 4 papers here · 3,308 citations](https://md.research.elamur.ai/free/en/authors/dat-quoc-nguyen/) · [🧑‍🔬**Jing Jiang** University of Technology Sydney 3 papers here · 3,169 citations](https://md.research.elamur.ai/free/en/authors/jing-jiang/) · [🧑‍🔬**Yufei Wang** Monash University 4 papers here · 3,117 citations](https://md.research.elamur.ai/free/en/authors/yufei-wang/) · [🧑‍🔬**Gholamreza Haffari** Monash University 7 papers here · 2,227 citations](https://md.research.elamur.ai/free/en/authors/gholamreza-haffari/)

[See all 53 people →](https://md.research.elamur.ai/free/en/countries/australia/people/)

## Works in our library (116)

Works of its institutions, the most cited first.

1. [**SciPy 1.0 — Fundamental Algorithms for Scientific Computing in Python**Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, et al.*2019 · 38,317 citations*](https://md.research.elamur.ai/free/en/papers/virtanen-2019-scipy-1-0-fundamental-algorithms/)
2. [**C4.5: Programs for Machine Learning**J. Ross Quinlan*1993 · 23,781 citations*](https://md.research.elamur.ai/free/en/papers/quinlan-1993-c45-programs-machine-learning/)
3. [**A Comprehensive Survey on Graph Neural Networks**Zonghan Wu, Shirui Pan, Fengwen Chen, et al.*2019 · 10,295 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-comprehensive-survey-graph-neural-networks/)
4. [**Explanation in Artificial Intelligence: Insights from the Social Sciences**Tim Miller*2017 · 5,362 citations*](https://md.research.elamur.ai/free/en/papers/miller-2017-explanation-artificial-intelligence-insights-social/)
5. [**Unifying Large Language Models and Knowledge Graphs: A Roadmap**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/)
6. [**NLTK: The Natural Language Toolkit**Steven Bird*2006 · 1,372 citations*](https://md.research.elamur.ai/free/en/papers/bird-2006-nltk-natural-language-toolkit/)
7. [**Vision-and-Language Navigation: Interpreting visually-grounded navigation instructions in real environments**Peter Anderson, Qi Wu, Damien Teney, et al.*2017 · 1,346 citations*](https://md.research.elamur.ai/free/en/papers/anderson-2017-vision-language-navigation-interpreting-visually/)
8. [**A Comprehensive Overview of Large Language Models**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,286 citations*](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/)
9. [**BERTweet: A pre-trained language model for English Tweets**Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen*2020 · 1,139 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2020-bertweet-pre-trained-language-model/)
10. [**A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network**Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, et al.*2018 · 944 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2018-novel-embedding-model-knowledge-base/)
11. [**Findings of the 2016 Conference on Machine Translation**Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al.*2016 · 936 citations*](https://md.research.elamur.ai/free/en/papers/bojar-2016-findings-2016-conference-machine-translation/)
12. [**Automatic Evaluation of Topic Coherence**David Newman, Jey Han Lau, Karl Grieser, et al.*2010 · 823 citations*](https://md.research.elamur.ai/free/en/papers/newman-2010-automatic-evaluation-topic-coherence/)
13. [**An Improved Non-monotonic Transition System for Dependency Parsing**Matthew Honnibal, Mark Johnson*2015 · 749 citations*](https://md.research.elamur.ai/free/en/papers/honnibal-2015-improved-non-monotonic-transition-system/)
14. [**langid.py: An Off-the-shelf Language Identification Tool**Marco Lui, Timothy Baldwin*2012 · 695 citations*](https://md.research.elamur.ai/free/en/papers/lui-2012-langid-py-off-shelf-language/)
15. [**Cross-lingual Name Tagging and Linking for 282 Languages**Xiaoman Pan, Boliang Zhang, Jonathan May, et al.*2017 · 668 citations*](https://md.research.elamur.ai/free/en/papers/pan-2017-cross-lingual-name-tagging-linking/)
16. [**Wide-Coverage Efficient Statistical Parsing with CCG and Log-Linear Models**Stephen Clark, James R. Curran*2007 · 625 citations*](https://md.research.elamur.ai/free/en/papers/clark-2007-wide-coverage-efficient-statistical-parsing/)
17. [**Lexical Normalisation of Short Text Messages: Makn Sens a #twitter**Bo Han, Timothy Baldwin*2011 · 586 citations*](https://md.research.elamur.ai/free/en/papers/han-2011-lexical-normalisation-short-text-messages/)
18. [**PhoBERT: Pre-trained language models for Vietnamese**Dat Quoc Nguyen, Anh Tuan Nguyen*2020 · 571 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2020-phobert-pre-trained-language-models/)
19. [**SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles**Su Nam Kim, Olena Medelyan, Min-Yen Kan, et al.*2010 · 459 citations*](https://md.research.elamur.ai/free/en/papers/kim-2010-semeval-2010-task-5-automatic/)
20. [**Graph-to-Sequence Learning using Gated Graph Neural Networks**Daniel Beck, Gholamreza Haffari, Trevor Cohn*2018 · 456 citations*](https://md.research.elamur.ai/free/en/papers/beck-2018-graph-sequence-learning-gated-graph/)
21. [**GPT-NER: Named Entity Recognition via Large Language Models**Shuhe Wang, Xiaofei Sun, Xiaoya Li, et al.*2025 · 436 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-gpt-ner-named-entity-recognition/)
22. [**Self-Alignment Pretraining for Biomedical Entity Representations**Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, et al.*2021 · 432 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-self-alignment-pretraining-biomedical-entity/)
23. [**Offline bilingual word vectors, orthogonal transformations and the inverted softmax**Samuel L. Smith, David H. P. Turban, Steven Hamblin, et al.*2017 · 426 citations*](https://md.research.elamur.ai/free/en/papers/smith-2017-offline-bilingual-word-vectors-orthogonal/)
24. [**Iterative Back-Translation for Neural Machine Translation**Vu Cong Duy Hoang, Philipp Koehn, Gholamreza Haffari, et al.*2018 · 420 citations*](https://md.research.elamur.ai/free/en/papers/hoang-2018-iterative-back-translation-neural-machine/)
25. [**Harnessing Context Incongruity for Sarcasm Detection**Aditya Joshi, Vinita Sharma, Pushpak Bhattacharyya*2015 · 415 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2015-harnessing-context-incongruity-sarcasm-detection/)

[See all 116 works →](https://md.research.elamur.ai/free/en/countries/australia/works/)

## Topics

Topics of its works in our library, with the number of works on each.

[Machine translation (13)](https://md.research.elamur.ai/free/en/topics/machine-translation/) · [Evaluation & benchmarks (13)](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Language models & pretraining (12)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Semitic languages (11)](https://md.research.elamur.ai/free/en/topics/semitic-languages/) · [Sentiment & emotion (9)](https://md.research.elamur.ai/free/en/topics/sentiment-emotion/) · [Syntax & grammar formalisms (7)](https://md.research.elamur.ai/free/en/topics/syntax-grammar/) · [Dialogue systems (6)](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · [Hebrew & Aramaic (6)](https://md.research.elamur.ai/free/en/topics/hebrew-aramaic/) · [Speech act theory (5)](https://md.research.elamur.ai/free/en/topics/speech-act-theory/) · [Coreference resolution (5)](https://md.research.elamur.ai/free/en/topics/coreference-resolution/) · [Named entity recognition (4)](https://md.research.elamur.ai/free/en/topics/named-entity-recognition/) · [Multilingual & cross-lingual NLP (4)](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · [Low-resource languages (4)](https://md.research.elamur.ai/free/en/topics/low-resource-languages/) · [Morphology (4)](https://md.research.elamur.ai/free/en/topics/morphology/) · [Knowledge graphs & ontologies (4)](https://md.research.elamur.ai/free/en/topics/knowledge-graphs/) · [Discourse analysis (3)](https://md.research.elamur.ai/free/en/topics/discourse-analysis/) · [Question answering (3)](https://md.research.elamur.ai/free/en/topics/question-answering/) · [Bias, fairness & safety (3)](https://md.research.elamur.ai/free/en/topics/bias-fairness-safety/) · [Vision & language (3)](https://md.research.elamur.ai/free/en/topics/multimodal/) · [Dependency parsing (2)](https://md.research.elamur.ai/free/en/topics/dependency-parsing/) · [Treebanks (2)](https://md.research.elamur.ai/free/en/topics/treebanks/) · [Historical linguistics & language change (2)](https://md.research.elamur.ai/free/en/topics/language-change/) · [Word sense disambiguation (1)](https://md.research.elamur.ai/free/en/topics/word-sense-disambiguation/) · [Information extraction (1)](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Speech & spoken language (1)](https://md.research.elamur.ai/free/en/topics/speech/) · [Code & programming languages (1)](https://md.research.elamur.ai/free/en/topics/code-and-programming/) · [Semantic parsing & meaning representation (1)](https://md.research.elamur.ai/free/en/topics/semantic-parsing/) · [Psycholinguistics & language acquisition (1)](https://md.research.elamur.ai/free/en/topics/psycholinguistics/)

## Fields

[Linguistics & languages (66)](https://md.research.elamur.ai/free/en/shelves/linguistics/) · [Natural language processing (41)](https://md.research.elamur.ai/free/en/shelves/nlp/) · [Machine translation (12)](https://md.research.elamur.ai/free/en/shelves/machine-translation/) · [AI & machine learning (9)](https://md.research.elamur.ai/free/en/shelves/ai/) · [Computing & GPUs (4)](https://md.research.elamur.ai/free/en/shelves/computing/) · [Mathematics & statistics (2)](https://md.research.elamur.ai/free/en/shelves/mathematics/)

## Works by year

20,102,020

- [← back to](https://md.research.elamur.ai/free/en/countries/) — countries