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 recently presented papers on this project at AAAI'12 and Computational Sustainability 2012.
Office: Park 249
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.
In Fall 2013, I'll be moving to the University of
I have an Opening for a Postdoctoral Research Assistant at Penn.
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
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
- Paul Ruvolo (Postdoc): lifelong learning, knowledge transfer
- Caitlyn Clabaugh (BS 2013, Bryn Mawr College): learning to create automatic A vs B music mashups
- Rose Abernathy (BS 2013, Haverford College):
- Meagan Neal (BS 2013, Bryn Mawr College): active multi-task learning
- Jacy Li (BS 2014, Bryn Mawr College): lifelong
- Rachel Li (BS 2014, Bryn Mawr College):
relational community detection using Gaussian processes
- Fangyu Xiong (BS 2015, Haverford College):
lifelong object recognition
- Leila Zilles (BS 2012, Bryn Mawr College):
active transfer learning for sparse language translation
(now 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
- Ben Cutilli (BS 2012, Haverford College): vision and UGV control in USARsim
- Steven Gutstein (Postdoc 2011-2012): lifelong
learning, knowledge transfer
- Kerstin Baer (BS 2011, Bryn Mawr College):
continual knowledge transfer (now at Stanford under an
NSF Grad Fellowship)
- Alexandra Lee (BS 2011, Bryn Mawr College): visualizing community detection (now at UWashington)
- Rachael Mansbach (BS 2011, Swarthmore College):
interactive community detection (now at UIUC)