Eric Eaton
Research Associate Professor, CIS
“Eric Eaton is a faculty member in the Department of Computer and Information Science at the University of Pennsylvania, and a member of the GRASP (General Robotics Automation, Sensing, Perception) lab. Prior to joining Penn, he was a Visiting Assistant Professor in the computer science department at Bryn Mawr College. His primary research interests lie in the fields of machine learning, artificial intelligence, and data mining with applications to robotics, search & rescue, environmental sustainability, and medicine. In particular, his research focuses on developing versatile AI systems that can learn multiple tasks over a lifetime of experience in complex environments, transfer learned knowledge to rapidly acquire new abilities, and collaborate effectively with humans and other agents through interaction. This research is funded by grants from the Office of Naval Research, the National Science Foundation, and Lockheed Martin.
Before moving into academia, Eric spent two years as a senior research scientist at Lockheed Martin Advanced Technology Laboratories working in applied research. At Lockheed Martin ATL, he led a number of machine learning research projects in the Artificial Intelligence Lab with a focus on their application for a variety of DoD organizations. While at Lockheed Martin, he was also part-time faculty in computer science at Swarthmore College.
Eric received his Ph.D. in computer science from the University of Maryland, Baltimore County (UMBC), focusing on artificial intelligence and machine learning. His dissertation developed methods for selective knowledge transfer between learning tasks and was advised by Marie desJardins. At UMBC, he was a member of the Multi-Agent Planning and LEarning (MAPLE) research group and also a part-time instructor.”
Research Areas
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Research Groups
Publications
Expert-augmented machine learning
Publisher National Academy of Sciences
Reply to Nock and Nielsen: On the work of Nock and Nielsen and its relationship to the additive tree
Publisher National Academy of Sciences
Using task descriptions in lifelong machine Learning for Improved Performance and Zero-Shot Transfer
Publisher Journal of Artificial Intelligence Research (JAIR)
Publisher arXiv
Artificial intelligence for pediatric ophthalmology
Publisher Lippincott Williams & Wilkins (LWW)
Building more accurate decision trees with the additive tree
Publisher National Academy of Sciences
Deep lifelong reinforcement learning for resilient control and coordination
Publisher University of Pennsylvania
Deep transfer learning for few-shot SAR image classification
Publisher Multidisciplinary Digital Publishing Institute (MDPI)
Learning shared knowledge for deep lifelong learning using deconvolutional networks
Publisher International Joint Conference on Artificial Intelligence (IJCAI)
Publisher Elsevier
SAR image classification using few-shot cross-domain transfer learning
Publisher IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR)
Transfer Learning via Minimizing the Performance Gap Between Domains
Publisher Advances in Neural Information Processing Systems
A recap of the AAAI / IAAI 2018 conferences and the EAAI symposium
Publisher AI Access Foundation
Publisher AI Matters
Lifelong inverse reinforcement learning
Publisher Conference on Neural Information Processing Systems
Lifelong learning networks: Beyond single agent lifelong learning
Publisher AAAI Press
Modeling consecutive task learning with task graph agendas
Publisher International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Multi-agent distributed lifelong learning for collective knowledge acquisition
Publisher International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Publisher AI Matters
AI Profiles: An Interview with Maja Mataric
Publisher AI Matters
Publisher arXiv
Lifelong Learning with Gaussian Processes
Publisher Lecture Notes in Computer Science (LNCS)
Teaching integrated ai through interdisciplinary project-driven courses
Publisher AI Magazine
Tree-structured boosting- Connections between gradient stumps and full decision trees
Publisher arXiv
Design of a Low-Cost Platform for Autonomous Mobile Service Robots
Publisher International Joint Conference on Artificial Intelligence (IJCAI)
Lifelong Learning for Disturbance Rejection on Mobile Robots
Publisher IEEE International Conference on Intelligent Robots and Systems (IROS)
Publisher Scientfic Reports
Online Contrastive Divergence with Generative Replay: Experience Replay without Storing Data
Publisher arXiv
Using Task Features for Zero-Shot Knowledge Transfer in Lifelong Learning
Publisher International Joint Conference on Artificial Intelligence (IJCAI)
Publisher AI Matters
Work in Progress: Lifelong Learning for Disturbance Rejection on Mobile Robots
Publisher International Conference on Autonomous Agents and Multiagent Systems (AAMAS)
Autonomous Cross-Domain Knowledge Transfer in Lifelong Policy Gradient Reinforcement Learning
Publisher International Joint Conference on Artificial Intelligence (IJCAI)
Reports on 2015 AAAI Workshop Program
Publisher AI Magazine
Safe Policy Search for Lifelong reinforcement learning with sublinear regret
Publisher IEEE International Conference on Robotics and Automation (ICRA)
News
Students
Research Staff
Alumni
Research Areas
- Service Robots
- Perception
- Vision
- Data-Driven Control Algorithms
- Autonomy
- Machine Learning