Eric Eaton

Eric Eaton is a Research Associate Professor in the Department of Computer and Information Science at the University of Pennsylvania and a member of the GRASP Laboratory. His work focuses on building versatile AI and robotic systems capable of learning continually over long time horizons, transferring knowledge across tasks, and acquiring new skills efficiently in complex and dynamic environments. Eaton’s research integrates machine learning, artificial intelligence, data mining, stochastic control, and multi-agent coordination, with applications in robotics, search and rescue operations, environmental sustainability, medical video analysis, and autonomous navigation. A significant thread of his work advances lifelong machine learning, including selective knowledge transfer, neural composition for reinforcement learning, and scalable frameworks for multi-task and multi-agent continual learning. Prior to joining Penn, Eaton was a senior research scientist at Lockheed Martin Advanced Technology Laboratories, where he led AI and ML research initiatives for DoD applications, and taught part-time at Swarthmore College. He earned his Ph.D. in Computer Science from the University of Maryland, Baltimore County, where he investigated transfer learning in multi-agent systems. His research is supported by agencies such as ONR, NSF, and Lockheed Martin.