Chelsea Finn is an American computer scientist and researcher. She is an associate professor of computer science at Stanford University and a research scientist at Google Brain, leading the IRIS (Intelligence through Robotic Interaction at Scale) lab.
Meta-Learning and MAML
Finn earned her Ph.D. in Computer Science from UC Berkeley in 2018, where she was advised by Pieter Abbeel and Sergey Levine. Her doctoral dissertation was a milestone, introducing Model-Agnostic Meta-Learning (MAML). MAML is a foundational algorithm in meta-learning (learning to learn) that allows neural networks to adapt to new tasks with very few training examples, mimicking human adaptability.
Robotics and Generalization
Finn's work at Stanford focuses on enabling robots to acquire general utility behaviors through unsupervised interaction and meta-learning, showing how robots can learn to handle new objects and environments without explicit programming.
