Stanford University
University of Amsterdam
University of Oxford
David PfauFounding Member of Technical Staff · PrometheusResearcher↗
Founder · Researcher
Nal Kalchbrenner
PrometheusFounding Member
Kalchbrenner helped establish neural generation across several kinds of data: PixelCNN for images[1], WaveNet for high-fidelity speech[2], and ByteNet for parallel sequence processing[3]. He also contributed to AlphaGo and neural weather forecasting, showing how related learning ideas could transfer across very different domains.
Career & education
Current rolePrometheus2025-presentFounding Member
Prometheus2025-presentPreviously
Google DeepMind2014-2024Research Scientist
Google DeepMind2014-2024Work 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.
citations67,417As of Nov 9, '26
Updates 1
Selected contributions
Mastering the game of Go with deep neural networks and tree search
With David Silver, Aja Huang, Chris J. Maddison, Arthur Guez, Laurent Sifre, George van den Driessche, Julian Schrittwieser and others ·AlphaGo combined neural networks and search to beat a professional Go player.
WaveNet: A Generative Model for Raw Audio
With Aäron van den Oord, Sander Dieleman, Heiga Zen, Karén Simonyan, Oriol Vinyals, Alex Graves, Andrew Senior and others ·WaveNet generates natural-sounding speech directly as a sequence of audio samples.
References
- Neural Machine Translation in Linear Time — ByteNetresearch.google
Author list and abstract confirm ByteNet contribution and efficient sequence processing; parallelism refers to convolutional computation, not simultaneous autoregressive output generation.
Based on public sources. If accuracy is important, verify details using the links or references.
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Reviewed August 4, 2026 · Checked for accuracy and new information.
