Education and Research 

My most recent CV can be found here. 

My group, Foundations of Reinforcement Learning, focuses on designing algorithms and studying the theoretical foundations of sequential decision making, whose currently most advanced form is found in RL. 

Short Bio

Claire Vernade is a Group Leader at the University of Tübingen, within the Cluster of Excellence in Machine Learning for Science. She received an Emmy Noether award in 2022 and an ERC Starting Grant in 2024. Her research spans sequential decision making, including bandit problems and theoretical reinforcement learning, with a focus on principled learning algorithms. She won an Outstanding Paper Award at ICLR 2021 for her work on "Eigengame: PCA as a Nash Equilibrium." Claire previously worked as a Research Scientist at DeepMind and as a post-doc at the University of Magdeburg. She holds a PhD from Telecom ParisTech. Passionate about diversity and inclusivity in ML, Claire co-leads the Women in Learning Theory initiative and supports efforts to promote inclusivity in the tech industry.

Head shot

For talk announcement purposes, here are (non professional) headshots I am happy to share.