Raia Hadsell
TL;DR Raia Hadsell is a pioneering AI researcher known for her influential work in deep reinforcement learning, continual learning, and robotics.
Raia Hadsell is a leading researcher in artificial intelligence whose work spans robotic learning, deep reinforcement learning, and systems that learn continuously over time. She has played a key role in advancing AI that can adapt, reason, and operate safely in dynamic environments. Her contributions have shaped the evolution of modern robotics and long-term learning systems.
Raia Hadsell is a senior research leader at DeepMind, where she has helped guide major projects focused on lifelong learning and autonomous agents. Her research explores how AI systems can retain prior knowledge while acquiring new skills, a core challenge in building adaptable, robust intelligence. Earlier in her career, she contributed to pioneering neural network research at New York University and the French National Institute for Research in Computer Science and Automation.
At DeepMind, she has been instrumental in developing algorithms that allow agents to learn from experience, navigate complex environments, and generalize across tasks. Her work combines neuroscience-inspired methods, representation learning, and reinforcement learning. Beyond her technical contributions, she is a vocal advocate for interdisciplinary AI research and for developing systems that can work safely and meaningfully in the real world.
Senior research leader at DeepMind, guiding major work in continual learning and autonomous agents
Pioneering research on lifelong learning and knowledge retention in neural networks
Significant contributions to deep reinforcement learning and robotic navigation
Early career research at NYU and INRIA, advancing neural network methods
Influential voice in the development of AI systems that learn safely and adapt over time
Founder of interdisciplinary efforts connecting robotics, neuroscience, and machine learning
