Stephan Oepen

Professor, Head of Department - Department for Informatics
Image of Stephan Oepen
Norwegian version of this page
Mobile phone +47-4546 6632
Room OJD-4428
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Postal address Boks 1080 Blindern 0317 Oslo

Profile

Stephan Oepen studied Linguistics, German and Russian Philology, Computer Science, and Computational Linguistics at Berlin, Volgograd, and Saarbrücken.  Between 2011 and 2017, he headed the Research Group for Language Technology at the University of Oslo; in 2020 he served as the manager of the Divison for Machine Learning at the Department of Informatics; and has since been elected as Head of Department for the period 2021–24.

Prior to his current appointment, he worked, among others, at the German Research Center for Artificial Intelligence and Saarland University (both Germany), YY Technologies (Mountain View), and Stanford University (both USA).  His research revolves around the integration of linguistics and computing, where he has published some hundred peer-reviewed research articles and conference papers and has co-founded the world-wide DELPH-IN network and the Nordic Language Processing Laboratory (NLPL).  Oepen has supervised to completion ten doctoral projects and about twenty Master of Science degrees.

In 2020, he is president of the ACL Special Interest Group on Natural Language Parsing (SIGPARSE), chair of the CoNLL Shared Task on Meaning Representation Parsing, and area co-chair for the 58th Annual Conference of the Association for Computational Linguistics.  He has been a member of the editorial board of Computational Linguistics and of the executive committee of the European Association for Computational Linguistics, as well as secretary of SIGPARSE and area co-chair for the 2017 Conference of the European Chapter of the Association for Computational Linguistics and for the 2018 Conference on Empirical Methods in Natural Language Processing.  In the academic year 2017–18, Oepen has co-directed an international research group at the Center for Advanced Studies of the Norwegian Academy of Science and Letters.

In Press

 

Tags: language technology, Machine Learning
Published Nov. 4, 2010 2:12 PM - Last modified Feb. 9, 2021 8:04 PM