Ryan Cotterell
- Artificial Intelligence top 1%
- Natural Language Processing Techniques 83
- Topic Modeling 81
- Speech Recognition and Synthesis 14
- Speech and dialogue systems 13
- Text Readability and Simplification 12
- Algorithms and Data Compression 8
- Health Informatics top 10%
- Cultural Studies top 2%
- Language and cultural evolution 10
- Language and Linguistics top 5%
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- Neurobiology of Language and Bilingualism 9
- Co-authors
- Jason EisnerClara MeisterHinrich SchützeChristo KirovTiago PimentelMans HuldenShijie WuJohn Sylak-Glassman
- Journals
- Transactions of the Association for Computational Linguistics (14 papers)Proceedings of the National Academy of Sciences (1 paper)Nature Machine Intelligence (1 paper)
- Partner nations
- United StatesSwitzerlandUnited Kingdom
In The Last Decade
Ryan Cotterell
108 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 1.3k
- Health Informatics 15
- Cultural Studies 84
- Computer Vision and Pattern Recognition 201
- Language and Linguistics 75
Countries citing papers authored by Ryan Cotterell
This map shows the geographic impact of Ryan Cotterell's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ryan Cotterell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan Cotterell more than expected).
Fields of papers citing papers by Ryan Cotterell
This network shows the impact of papers produced by Ryan Cotterell. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ryan Cotterell. The network helps show where Ryan Cotterell may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ryan Cotterell, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 1 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 1 | |
| 6 | 2023 | 29 | |
| 7 | 2023 | 10 | |
| 8 | 2023 | 5 | |
| 9 | 2023 | 0 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 2 | |
| 12 | 2022 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2022 | 0 | |
| 15 | 2022 | 3 | |
| 16 | 2022 | 10 | |
| 17 | UniMorph 2.0: Universal Morphology | 2018 | 7 |
| 18 | 2017 | 7 | |
| 19 | Translations of the Callhome Egyptian Arabic corpus for conversational speech translation. | 2014 | 10 |
| 20 | A Multi-Dialect, Multi-Genre Corpus of Informal Written Arabic | 2014 | 55 |
About Ryan Cotterell
Ryan Cotterell is a scholar working on Artificial Intelligence, Computational Mathematics, Cultural Studies, Cognitive Neuroscience and General Social Sciences, having authored 130 papers that have together received 1.5k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (83 papers), Topic Modeling (81 papers), Speech Recognition and Synthesis (14 papers), Speech and dialogue systems (13 papers), Text Readability and Simplification (12 papers), Language and cultural evolution (10 papers), Neurobiology of Language and Bilingualism (9 papers) and Algorithms and Data Compression (8 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Health Informatics (15 citations), Cultural Studies (84 citations), Computer Vision and Pattern Recognition (201 citations) and Language and Linguistics (75 citations). Ryan Cotterell has collaborated with scholars based in United States, Switzerland and United Kingdom. Frequent co-authors include Jason Eisner, Clara Meister, Hinrich Schütze, Christo Kirov, Tiago Pimentel, Mans Hulden, Shijie Wu, John Sylak-Glassman, Chris Callison-Burch and Tim Vieira. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Proceedings of the National Academy of Sciences, Nature Machine Intelligence, Language Resources and Evaluation and Journal of Memory and Language.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.