🧑‍🔬 Yannis Assael

🏛️ Affiliations

🏢Google DeepMindLondon · United Kingdom2016–2025 · 10 papersEmployment 2017–2018 · Research ScientistEmployment 2018–2022 · Senior Research ScientistEmployment since 2022 · Staff Research Scientist🎓University of OxfordOxford · United Kingdom2013–2021 · 7 papersEducation 2013–2014 · MSc in Computer Science, Computer ScienceEducation 2015–2019 · DPhil in Machine Learning, Computer Science🏢GoogleLondon · United Kingdom2016–2025 · 2 papers🎓Imperial College LondonLondon · United Kingdom2014–2015Education 2014–2015 · MRes in Machine Learning, Computing🎓University of MacedoniaThessaloniki · Greece2008–2013Education 2008–2013 · Diploma, Applied Informatics🎓Anatolia CollegeThessaloniki · GreeceEducation

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

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

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Machine Learning for Ancient Languages: A Survey (2023 · 124 citations)
   This survey maps the published research applying machine learning to texts in ancient languages. It covers any script or writing medium from the first Mesopotamian writing (about 3400 BCE) to the end of the first millennium CE, and it leaves out pre-2000 studies and work that does not use ML. The authors organize the…
2. Evaluating Frontier Models for Dangerous Capabilities (2024 · 36 citations)
   Popular benchmarks measure broad skills such as coding or maths, and most safety tests check whether a model refuses harmful requests.

All works

6 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

1. Restoring and attributing ancient texts using deep neural networks ↗Nature 603, 280-283 · no summary yetYannis Assael et al.2022 · 250 citations
2. Machine Learning for Ancient Languages: A SurveyComputational LinguisticsThea Sommerschield, Yannis Assael, John Pavlopoulos, et al.2023 · 124 citations
3. Sample Efficient Adaptive Text-to-Speech ↗arXiv (Cornell University) · no summary yetYutian Chen et al.2018 · 111 citations
4. Restoring ancient text using deep learning: a case study on Greek epigraphy ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetYannis Assael, Thea Sommerschield, Jonathan Prag2019 · 92 citations
5. Evaluating Frontier Models for Dangerous CapabilitiesarXiv:2403.13793Mary Phuong, Matthew Aitchison, Elliot Catt, et al.2024 · 36 citations
6. Contextualizing ancient texts with generative neural networks ↗Nature 645 · no summary yetYannis Assael et al.2025 · 23 citations

🤝 Co-authors here

9 co-authors with a page, the most papers together first.

• Andrew Senior
• Chris Dyer
• Elliot Catt
• Ion Androutsopoulos
• John Pavlopoulos
• Mary Phuong
• Matthew Aitchison
• Matthew Rahtz
• Tom Lieberum

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Computational Linguistics: Computational Linguistics 2023
• Nature 603, 280-283
• Nature 645
• Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

🔗 Cited by

Papers of our library cite their works 163 times (of the 149,439 papers whose bibliographies we read); 35 citing papers with a page here →.

Updated 3 November 2026

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