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Mustafa Suleyman

Mustafa Suleyman has 2 papers in our library, in 2015; often with Charles Beattie, Edward Grefenstette, Karl Moritz Hermann.

2 papers in our library · 2015

OpenAlex · ORCID · Wikidata · h-index 18 · 53 works · 16,881 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,631 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #803

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🏢MicrosoftRedmond · United States2026 · 4 paperscurrent🏢Google DeepMindLondon · United Kingdom2015–2021 · 14 papersEmployment · Co-founder
🏛️Microsoft AI2024Employment since 2024
🏛️Greylock PartnersUnited StatesEmployment
🏛️Inflection AIUnited StatesEmployment
🏛️Queen Elizabeth's School, BarnetLondon Borough of Barnet · United KingdomEducation
🏛️Thornhill Primary SchoolLondon Borough of Islington · United KingdomEducation
🎓University of OxfordOxford · United KingdomEducation

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArts and Humanities · 1 workArtificial Intelligence · 2 worksInformation Systems · 1 workLanguage and Linguistics · 1 workHardware and Architecture · 1 work

💡 Concepts 3Key ideas and methods explained on our concept pages.Information extraction · 1 workNatural language understanding · 1 workQuestion answering · 1 work

 Works by year

2010s

20152 papers

 Papers

The most cited first (OpenAlex and our library).

  1. Teaching Machines to Read and Comprehend (2015 · 3,858 citations)
    Machine reading comprehension lacked large supervised datasets. Existing resources held only hundreds of examples, so research leaned on synthetic stories or unsupervised relation extraction. The authors convert CNN and Daily Mail news stories into document–query–answer triples. Each story comes with abstractive…
  2. Massively Parallel Methods for Deep Reinforcement Learning (2015 · 427 citations)
    DQN, the deep Q-learning agent that learns Atari 2600 games from raw pixels, had only been run on a single machine.

All works

3 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. Teaching Machines to Read and ComprehendarXiv:1506.03340Karl Moritz Hermann, Tomáš Kočiský, Edward Grefenstette, et al.2015 · 3,858 citations
  2. The Kinetics Human Action Video Dataset ↗arXiv (Cornell University) · no summary yetWill Kay et al.2017 · 2,839 citations
  3. Massively Parallel Methods for Deep Reinforcement LearningarXiv:1507.04296Arun Nair, Praveen Srinivasan, Sam Blackwell, et al.2015 · 427 citations

 Co-authors here

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

 Cited by

Papers of our library cite their works 1,631 times (of the 149,439 papers whose bibliographies we read); 321 citing papers with a page here →.

Updated

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