Rembrand
Amazon
University of Toronto
Alexis ConneauDistinguished Scientist · MetaResearcher↗3 shared research fields
Both at Meta
Researcher
Abdel-rahman Mohamed
MetaResearch Director
Mohamed helped establish deep neural networks for speech recognition and co-developed wav2vec 2.0, which learns speech patterns from untranscribed audio before seeing a small amount of labelled data.[1] That approach made accurate transcription possible for languages and settings with fewer human-written examples.
Career & education
Current roleMeta2025-presentResearch Director
Meta2025-presentWork and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations77,456As of Oct 20, '26
citations+3,988Since last snapshot, Jul 1, '26
Selected contributions
Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups
With Geoffrey Hinton, Li Deng, Dong Yu, George Dahl, Navdeep Jaitly, Andrew Senior, Vincent Vanhoucke and others ·Reviewed how deep neural networks improved the recognition of speech from recorded audio.
References
- wav2vec 2.0arxiv.org
Mohamed and colleagues show how learning from untranscribed audio can reduce the amount of labeled data needed for speech recognition.
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Reviewed August 8, 2026 · Checked for accuracy and new information.
