Fall 2013: CIS 110 - Introduction to Computer Science
Spring 2013: CMSC 380 - Relational Network Analysis
Spring 2013: CMSC 246 - Programming Paradigms
Fall 2012: CMSC 206 - Data Structures
Fall 2012: CMSC 110 - Introduction to Computing
Spring 2012: CMSC 372 - Artificial Intelligence
Spring 2012: CMSC 206 - Data Structures
Past courses taught at Bryn Mawr, Swarthmore, and UMBC
I'm happy to announce the online textbook Artificial Intelligence for Computational Sustainability: A Lab Companion with Doug Fisher, Bistra Dilkina, and Carla Gomes. This is an experiment in crowd-sourced textbook creation, intended to supplement an AI course with assignments related to sustainability. We presented papers on this project at AAAI'12 and Computational Sustainability 2012.
Office: Levine 264
Office Hours (Fall 2013):
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.
Further details are provided in his curriculum vitae.
My primary research interests are in the areas of artificial intelligence and machine learning, with a focus on the following topics:
- Lifelong learning of multiple sequential tasks over long time scales,
- Knowledge transfer between learning tasks, and
- Interactive AI methods that combine
system-driven active learning with extensive user-driven
control over learning and reasoning processes.
I am also interested in applications of AI to medicine, search and rescue, and space exploration.
Details of my research on these topics can be found on my research and publications pages. This research has also produced a number of software packages, which I make freely available for academic and not-for-profit use.
This research is currently funded by:
- ONR Grant #N00014-11-1-0139, PI (Co-PI: Terran Lane)
- ONR Contract #N00014-10-C-0192 via Lockheed Martin ATL, PI
Haitham Bon Ammar will be joining my research group and the GRASP lab in November. Welcome, Haitham!
I have an Opening
for a Postdoctoral Research Assistant at Penn. Thank you for your interest, but the postdoc position has been filled.
Paul Ruvolo will be leaving his postdoc to become an Assistant Professor at Olin College. Congratulations, Paul!
In March 2013, I chaired the AAAI 2013 Spring Symposium on
Lifelong Machine Learning.
Students and Postdocs
I've been fortunate to work with a number of talented
students on these research projects.
Current Research Assistants
- Fangyu Xiong (BS 2015, Haverford College):
lifelong object recognition
- Gabriel Ryan (BS 2013, Swarthmore College):
lifelong RL with Horde
Alumni and Former Students
Ruvolo (Postdoc 2012-2013, Bryn Mawr College): lifelong learning,
(Continued to a faculty position at Olin College as an Assistant Professor)
- Jacy Li (BS 2014, Bryn Mawr College): lifelong learning
- Rachel Li (BS 2014, Bryn Mawr College): relational community detection using Gaussian processes
- Caitlyn Clabaugh (BS 2013, Bryn Mawr College):
learning to create automatic A vs B music mashups
(Continued to PhD studies at USC)
- Rose Abernathy (BS 2013, Haverford College): social gaming
- Meagan Neal (BS 2013, Bryn Mawr College): active multi-task learning
- Ben Cutilli (BS 2013, Haverford College): vision and UGV control in USARsim
- Leila Zilles (BS 2012, Bryn Mawr College):
active transfer learning for sparse language translation
(Continued to PhD studies at UWashington under an NSF Grad Fellowship)
- David Wilikofsky (BS 2012, Swarthmore College): bootstrapping RL with human demonstration
- Emily Levine (BS 2012, Bryn Mawr College): learning to predict Parkinson's At Risk Syndrome
- Steven Gutstein (Postdoc 2011-2012): lifelong learning, knowledge transfer (Continued to work for JPMorgan)
- Kerstin Baer (BS 2011, Bryn Mawr College):
continual knowledge transfer
(Continued to PhD studies at Stanford under an NSF Grad Fellowship)
- Alexandra Lee (BS 2011, Bryn Mawr College):
visualizing community detection
(Continued to a Masters program at UWashington)
- Rachael Mansbach (BS 2011, Swarthmore College):
interactive community detection
(Continued to PhD studies at UIUC)