Raia Hadsell

Timeline

1. 2006

   Learning an invariant mapping

   In 2006, she coauthors the CVPR paper Dimensionality Reduction by Learning an Invariant Mapping, which maps images to a low-dimensional representation with invariance to illumination or other factors. Her early work on contrastive loss anticipates techniques now central to embeddings, image recognition and multimodal retrieval.

2. By 2009

   A PhD with Yann LeCun

   After a Reed College degree in religion and philosophy, she turns to computer science and earns a PhD with Yann LeCun at NYU, working on Siamese neural networks and deep learning for mobile robots. Her thesis, Learning Long-range vision for offroad robots, wins the Outstanding Dissertation award in 2009.

3. 2014

   Joining DeepMind in London

   She does a postdoc at the Carnegie Mellon Robotics Institute with Drew Bagnell and Martial Hebert, then becomes a research scientist in SRI International's Vision and Robotics group in Princeton, New Jersey. She moves to London to join DeepMind in early 2014, where her research covers continual and transfer learning, deep reinforcement learning and neural models of navigation.

4. 2016–2017

   Fighting catastrophic forgetting

   In 2016, she is a coauthor of Progressive Neural Networks, which are immune to forgetting and reuse earlier features through lateral connections. Overcoming catastrophic forgetting in neural networks, also from 2016, slows learning on the weights important for earlier tasks, and DeepMind names the method Elastic Weight Consolidation in a March 2017 blog post. Her 2016 paper Learning to Navigate in Complex Environments trains agents in 3D mazes with auxiliary depth prediction and loop closure tasks.

5. 2022–2023

   Co-founding TMLR

   With Kyunghyun Cho and Hugo Larochelle, she co-founds the open journal Transactions on Machine Learning Research in 2022 and serves as a founding editor-in-chief through 2023. Her title at DeepMind in 2022 is Senior Director of Research and Robotics.

6. 2024

   VP of Research at DeepMind

   In 2024, she is a VP of Research at DeepMind and oversees the strategy for its exploratory research efforts. She gives an ICLR 2024 invited talk, Learning through AI's winters and springs: unexpected truths on the road to AGI, drawing on 20 years as an AI researcher and leader.

7. November 2025–March 2026

   UK government AI ambassador

   In November 2025, the UK government names her one of its new AI ambassadors, to champion the UK's place at the forefront of AI innovation and security. In March 2026, she chairs the peer review panel that assesses applications for the government's Fundamental AI Research Lab.

8. As of October 2026

   Frontier AI at Google DeepMind

   She is a VP of Research at Google DeepMind and co-leads its Frontier AI unit. Her work includes DeepMind's weather prediction models GraphCast and GenCast, climate modeling, and the Genie world models.