Thomas Gammeltoft-Hansen

Thomas Gammeltoft-Hansen

Professor

Medlem af:


    1. 2023
    2. Accepteret/In press

      Danish Asylum Adjudication using Deep Neural Networks and Natural Language Processing

      Muddamsetty, S. M., Jahromi, M. N. S., Moeslund, T. B. & Gammeltoft-Hansen, Thomas, 2023, (Accepteret/In press) Danish Asylum Adjudication using Deep Neural Networks and Natural Language Processing. Springer, s. 1-13 14 s.

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    3. Udgivet

      On predicting and explaining asylum adjudication

      Piccolo, S. A., Gammeltoft-Hansen, Thomas, Katsikouli, Panagiota & Slaats, Tijs, 2023, ICAIL: International Conference on Artificial Intelligence and Law. Association for Computing Machinery, s. 217-226 10 s. (19th International Conference on Artificial Intelligence and Law, ICAIL 2023 - Proceedings of the Conference).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    4. 2021
    5. Udgivet

      Confronting Asylum Decision-making through Prototyping Sensemaking of Data and Participation

      Nielsen, Trine Rask, Katsikouli, Panagiota, Høgenhaug, Anna Murphy, Byrne, William Hamilton, Gammeltoft-Hansen, Thomas, Slaats, Tijs, Olsen, Henrik Palmer, Hildebrandt, Thomas Troels & Møller, Naja Holten, 2021, Proceedings of the 19th European Conference on Computer-Supported Cooperative Work, ECSCW 2021k: The International Venue on Practice-centred Computing on the Design of Cooperation Technologies, . European Society for Socially Embedded Technologies, 10 s. (Reports of the European Society for Socially Embedded Technologies; Nr. ECSCW, Bind 2021).

      Publikation: Bidrag til bog/antologi/rapportKonferencebidrag i proceedingsForskningfagfællebedømt

    6. Under udarbejdelse

      The Data Driven Future of International Refugee Law

      Byrne, William Hamilton & Gammeltoft-Hansen, Thomas, 2021, (Under udarbejdelse).

      Publikation: KonferencebidragPaperForskning

    ID: 926563