Lifelong Machine Learning
Lifelong learning is a key characteristic of human intelligence, enabling us to continually acquire and refine our knowledge and abilities over a lifetime of experience across diverse domains. However, lifelong learning for intelligent systems remains a largely unsolved problem.
The Lifelong Machine Learning Research Group, led by Eric Eaton seeks to develop a comprehensive approach to lifelong learning for autonomous systems. The group’s research addresses fundamental issues of continual learning and transfer across diverse tasks, scalable knowledge maintenance, self-directed learning, adaptation to changing environments with guaranteed performance and safety, and interaction with end-users and other agents. These techniques are applied to problems in autonomous service robots and precision medicine.
Research Associate Professor, CIS
Robotics MSE '17 - Software Engineer, Waymo
Robotics MSE '14; PhD, CIS '17
PostDoc, CIS "13-'14 - Reinforcement Learning Team Leader, Huawei
Post Doc, CIS '18 - Simons Foundation
PostDoc, CIS '16 - Research Associate, Perelman School of Medicine UPenn
Robotics MSE '16, PhD ESE'19
Robotics MSE '18 - Software Engineer, NVIDIA
Robotics MSE '18 - Advanced AI Engineer, Honeywell
Robotics MSE '18 - Rivian
Robotics MSE '15 - Yelp
Robotics MSE '17 - COSY