Claire Vernade
Claire Vernade is a machine-learning researcher who works on sequential decision making, mainly bandit problems and theoretical reinforcement learning. She received her PhD from Telecom ParisTech in 2017, then worked as a research scientist at DeepMind in London from November 2018 to December 2022. Her joint paper EigenGame: PCA as a Nash Equilibrium won an Outstanding Paper Award at ICLR 2021. She was awarded an Emmy Noether junior research group in 2022 and an ERC Starting Grant in 2024. She is a full professor of Foundations of Machine Learning at the University of Technology Nuremberg since October 2025.
- Works
- 44
- Citations
- 343
- h-index
- 9
Publication numbers from OpenAlex, as of 15 October 2026.
Timeline
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2017
A doctorate from Telecom ParisTech
She receives her PhD from Telecom ParisTech in October 2017.
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November 2018–December 2022
Research scientist at DeepMind
From November 2018 to December 2022, she works as a research scientist at DeepMind in London, in the Foundations team.
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2021
An ICLR outstanding paper
Her joint paper EigenGame: PCA as a Nash Equilibrium receives an Outstanding Paper Award at ICLR 2021.
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2022
An Emmy Noether research group
In the 2022 DFG call she wins an Emmy Noether Independent Junior Research Group.
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January 2023
A Tübingen research group
In January 2023 she takes over the lead of a new research group in Tübingen. Her work on sequential decision making spans bandit problems and theoretical reinforcement learning.
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2024
An ERC Starting Grant
In 2024 she receives an ERC Starting Grant of around 1.25 million euros over five years.
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Since October 2025
A full professorship in Nuremberg
She is a full professor of Foundations of Machine Learning at the University of Technology Nuremberg since October 2025.
Sources and credits
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