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Prof. Dr. Günter Neumann

Contact +49 681 85775 5298 (Saarbrücken)

http://www.dfki.de/~neumann
Address (Berlin) Address (Saarbrücken) Gebäude D3 2Stuhlsatzenhausweg 3D-66123 Saarbrücken
Prof. Dr. Günter Neumann

Publications

Noon Pokaratsiri; Saadullah Amin; Günter Neumann (Hrsg.)

Workshop on Graph-Based Natural Language Processing (TextGraphs-17), ACL, 2024.

To the publication

Stalin Varanasi; Muhammad Umer Butt; Günter Neumann

In: Large Language Models for Natural Language Processing. International Conference on Recent Advances in Natural Language Processing (RANLP-2023), located at RANLP, September 4-6, Varna, Bulgaria, Pages 1171-1179, ISBN ISBN 978-954-452-092-2, INCOMA Ltd. Shoumen, BULGARIA, 9/2023.

To the publication

Tanja Bäumel; Soniya Vijayakumar; Josef van Genabith; Günter Neumann; Simon Ostermann

In: Yonatan Belinkov; Sophie Hao; Jaap Jumelet; Najoung Kim; Arya McCarthy; Hosein Mohebbi (Hrsg.). Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP. Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP-2023), Singapore, Pages 261-270, Association for Computational Linguistics, 2023.

To the publication

Profile

Short biography

Günter Neumann is a principal researcher and Research Fellow at DFKI and professor for Computational Linguistics at the Saarland University. Neumann works in the Multilinguality and Language Technology research area at the German Research Center for Artificial Intelligence (DFKI).

He studied Computer Science, Computational Linguistics, and Artificial Intelligence, and obtained a PhD in Computer Science in 1994, and the Venia Legendi in Computational Linguistics in 2004, both from the Saarland University.
He was appointed apl. professor in 2014 from the Saarland University.
He has been working and extensively publishing in different areas of Computational Linguistics and Artificial Intelligence. Together with his team members, he has successfully participated at numerous international scientific challenges in the area of cross-lingual question answering, textual entailment, and fact verification with very good results (e, g., top rankings of their systems at CLEF, TAC and Fever 2.0).
Günter is a member of the standing reviewing committee of the Transactions of the Association for Computational Linguistics (TACL).
He was a member in several program committees for international conferences (e.g., AAAI, ACL, EACL, NAACL, Coling, EMNLP, LREC) and workshops related to Natural Language Parsing, Text Analytics, and ontology-based information extraction. Günter was a guest researcher at Stanford, CMU and M.I.T.
He has a more than 30 years professional experience in research software development, and has lead several governmental (EU and national) and industrial funded projects in the area of language technology, information extraction, text analytics, and question answering.

  • PERKS

    Eliciting and Exploiting Procedural Knowledge in Industry 5.0

    The PERKS project supports the holistic governance of industrial PK in its entire life cycle, from elicitation to management and from access to exploitation. PERKS bases its solutions on leading-edge…

    PERKS
  • DAM-S

    Semantische Suche für das "Meere Online"-Portal der Deutschen Allianz Meeresforschung

    Entwicklung einer semantischen, KI-gestützten Suchfunktion für das Portal "Meere Online" für die Deutsche Allianz Meeresforschung (DAM)

     

  • PRECISE4Q

    Personalised Medicine by Predictive Modeling in Stroke for better Quality of Life

    Stroke is one of the most severe medical problems with far-reaching public health and socio-economic impact, gathering momentum in an ageing society. PRECISE4Q sets out to minimise the burden of…

    PRECISE4Q
  • iREAD

    Personalised Reading Apps for Primary School Children

    The overarching aim of the iRead project is to develop a software infrastructure of personalised, adaptive technologies and a diverse set of applications for supporting learning and teaching of…

    iREAD
  • Excitement

    EXploring Customer Interactions through Textual EntailMENT

    Identifying semantic inference relations between texts is a major underlying language processing task, needed in practically all text understanding applications. For example, Question Answering and…

    Excitement
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