Roman Klinger

University of Stuttgart

Names

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

Roman Klinger (Preferred)

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.

****@romanklinger.de
,
****@ims.uni-stuttgart.de

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.

Associate Professor
University of Stuttgart (uni-stuttgart.de)
2014Present
 
Visiting Researcher
University of Massachusetts, Amherst (umass.edu)
20132013
 
Postdoc
Bielefeld University (uni-bielefeld.de)
20122013
 
Postdoc
Fraunhofer SCAI (scai.fraunhofer.de)
20112012
 
Visiting Scholar
University of Massachusetts, Amherst (umass.edu)
20102010
 
PhD student
TU Dortmund (tu-dortmund.de)
20062010
 
PhD student
Fraunhofer SCAI (scai.fraunhofer.de)
20062010
 
Undergrad student
TU Dortmund (tu-dortmund.de)
19992006
 

Advisors, Relations & Conflicts

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

PhD Advisee
Evgeny Kim
****@gmail.com
20172020
 
PhD Advisee
Jeremy Barnes
****@ehu.eus
20182018
 
Postdoc Advisor
Philipp Cimiano
****@cit-ec.uni-bielefeld.de
20132014
 
Postdoc Advisor
Andrew McCallum
****@cs.umass.edu
20132013
 
PhD Advisor
Sebastian Riedel
****@cs.ucl.ac.uk
20102010
 
PhD Advisor
Günter Rudolph
****@tu-dortmund.de
20062010
 
PhD Advisor
Martin Hofmann-Apitius
****@scai.fraunhofer.de
20062010
 

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

machine learning
Present
 
probabilistic graphical models
Present
 
natural language processing
Present
 
emotion analysis
Present
 
sentiment analysis
Present
 
social media analysis
Present
 
digital humanities
Present