Teaching
Spring 2012: CMSC
372 -
Artificial Intelligence
Spring 2012: CMSC
206
- Data Structures
Past courses taught at Bryn Mawr, Swarthmore, and UMBC
Contact Information
|
Mailing Address: |
Office: Park 249 |
About Eric
Eric Eaton is a visiting assistant professor in the computer science department at Bryn Mawr College. Prior to joining Bryn Mawr College, he was a senior research scientist in the Artificial Intelligence research group at Lockheed Martin Advanced Technology Laboratories and part-time faculty 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.
Research
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
Students and Postdocs
I currently have openings for a Postdoctoral Research
Fellow in machine learning and several Summer Undergraduate or Graduate
Research Assistants.
I've been fortunate to work with a number of talented
students on
these research projects.
Current Research Assistants
- Steven Gutstein (Postdoc): lifelong learning, knowledge transfer
- Leila Zilles (BS 2012, Bryn Mawr College):
interactive
transfer learning for sparse language translation
- Emily Levine (BS 2012, Bryn Mawr College):
transfer learning to predict Parkinson's At Risk
Syndrome
- Ben Cutilli (BS 2012, Haverford College): vision
and learning in USARsim
- Stephanie Tran (BS 2013, Bryn Mawr College): learning for search and rescue in USARsim
Alumni
- Kerstin Baer (BS 2011, Bryn Mawr College):
continual
knowledge transfer (now at Stanford)
- Alexandra Lee (BS 2011, Bryn Mawr College): visualizing community detection (now at UWashington)
- Rachael Mansbach (BS 2011, Swarthmore College):
interactive
community detection (now at CMU)