ERIC EATON

University of Pennsylvania

Names

How do you usually write your name as author of a paper? Also add any other names you have authored papers under.

ERIC EATON
,
Eric Eaton

Emails

Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.

****@seas.upenn.edu
,
****@cis.upenn.edu
,
****@umbc.edu

Education & Career History

Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.

Faculty
University of Pennsylvania (upenn.edu)
2013Present
 
Visiting Assistant Professor
Bryn Mawr College (brynmawr.edu)
20102013
 
Senior Research Scientist
Lockheed Martin Advanced Technology Laboratories (lockheedmartin.com)
20082010
 
PhD student
University of Maryland, Baltimore County (umbc.edu)
20032009
 

Advisors, Relations & Conflicts

Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.

Social
Claudia Schulz
****@ukp.informatik.tu-darmstadt.de
Present
 
Coworker
Peter Stone
****@cs.utexas.edu
Present
 
Coworker
Michael Littman
****@cs.brown.edu
Present
 
Coworker
Fei Sha
****@gmail.com
Present
 
Coworker
Satinder Singh Baveja
****@umich.edu
Present
 
Coworker
Kristen Grauman
****@cs.utexas.edu
Present
 
Coworker
George Konidaris
****@cs.brown.edu
Present
 
Coworker
Erik Learned-Miller
****@cs.umass.edu
Present
 
Coworker
Matthew E. Taylor
****@ualberta.ca
Present
 
PhD Advisor
Marie desJardins
****@simmons.edu
20022009
 

Expertise

For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing

lifelong learning, continual learning
Present
 
transfer learning, multi-task learning
Present
 
interactive AI, interactive ML, interpretable ML
Present
 
perception, robotics, robot learning, robotic control, high-level intelligence
Present
 
precision medicine, clinical decision support
Present