Simon Osindero
Also known as Simon Kayode Osindero
Simon Osindero is an artificial intelligence researcher at Google DeepMind. They completed a doctorate at University College London in 2004 with the dissertation Contrastive Topographic Models. In 2006 they co-wrote A Fast Learning Algorithm For Deep Belief Networks with Hinton and Teh, published in Neural Computation. TWIML introduced them as a staff research scientist at DeepMind in 2019. The compute-optimal training study they co-authored won a NeurIPS 2022 Outstanding Paper Award, and Genie: Generative Interactive Environments won the ICML 2024 Best Paper award.
- Now at
- Google DeepMind
- Works
- 86
- Citations
- 29,004
- h-index
- 29
Publication numbers from OpenAlex, as of 15 October 2026.
Timeline
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2004
Contrastive topographic models
They complete a doctorate at University College London in 2004 with the dissertation Contrastive Topographic Models.
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2006
A fast learning algorithm
They co-write A Fast Learning Algorithm For Deep Belief Networks with Hinton and Teh, published in Neural Computation in 2006.
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2019
Staff research scientist at DeepMind
TWIML introduces them as a staff research scientist at DeepMind on its AI Rewind 2018 episode in 2019.
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2022
A NeurIPS Outstanding Paper
They co-author An empirical analysis of compute-optimal large language model training, which receives a NeurIPS 2022 Outstanding Paper Award.
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2024
A best paper for Genie
They co-author Genie: Generative Interactive Environments, which wins the ICML 2024 Best Paper award.
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As of October 2026
At Google DeepMind
They work at Google DeepMind as an artificial intelligence researcher.
Sources and credits
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- Simon Osindero - Wikidata
- Simon Osindero - The Mathematics Genealogy Project
- Simon Osindero's Home-Page
- AI Rewind 2018: Trends in Reinforcement Learning | TWIML - The Voice of Machine Learning & AI
- NeurIPS 2022 Awards
- [2203.15556] Training Compute-Optimal Large Language Models
- ICML Oral Genie: Generative Interactive Environments
- [2402.15391] Genie: Generative Interactive Environments