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Information Systems and Applied Computer Sciences

Cognitive Systems

  1.  University of bamberg
  2. Faculties
  3. Information Systems and Applied Computer Sciences
  4. Subject groups
  5. Applied Computer Science
  6. Cognitive Systems
  7. Team
  8. Knoblach, Judith

Judith Knoblach

Judith Knoblach

Research Assistant

M. A.

Office: WE5/05.052
Office hours: by appointment

Phone:
Email:  judith.knoblach(at)uni-bamberg.de

 

Projekt:

KMU-KI-Erfahrungszentrum

since 2023Research Assistant at Cognitive System Chair, AI Research Lead at SME AI Experience Center 
2021 - 2023Research Engineer for Conversational AI and Knowledge Graphs at IAIS Dresden
2019 - 2021Dialog Engineer at semvox GmbH
2015 - 2019Master Speech and Communication
2010 - 2014Bachelor Cognitive Science and Linguistics

Main Research Interests

Explainable Artificial Intelligence (XAI) methods for deep learning-based audio classification, including example-based explanations and symbolic rule extraction, as well as human-centered evaluation of XAI through user studies on calibrated trust, uncertainty, cognitive engagement and decision-making.

Knoblach, J., Vogl, L., Wehnert, C., Carbon, C. C., Franz, J., & Schmid, U. (2026). The SME AI experience center: overcoming AI adoption barriers for SMEs in industrial production. KI-Künstliche Intelligenz, 40(1), 99-104.

Knoblach, J., Finzel, B., & Schmid, U. (2026). A Framework for Context-aware XAI in Human-AI Collaboration. In Contextualizing Explanations: Proceedings of the 3rd TRR 318 Conference. Bielefeld University Press.

Knoblach, J., Krockert, M., Voigt, E., et al. (Eds.). (2026). Proceedings of the Second Workshop on AI in Production. Otto-Friedrich University of Bamberg. https://doi.org/10.20378/irb-114337

Knoblach, J., Schmid, U., Goulão, M., Schmid, L., Vujošević Janičić, M., & Boudaoud, K. (2025). The impact of peers, mentors and role models on successful PhD studies. In Actions for Gender Balance in Informatics Across Europe (pp. 175-195). Cham: Springer Nature Switzerland.

Finzel, B., Knoblach, J., Thaler, A., & Schmid, U. (2024, November). Near hit and near miss example explanations for model revision in binary image classification. In International conference on intelligent data engineering and automated learning (pp. 260-271). Cham: Springer Nature Switzerland.

Knoblach, J., Acharya, N., Koranemkattil, B., Both, A., & Collarana, D. (2022, October). Combining Knowledge Graphs and Language Models to Answer Questions over Tables. In SEMANTiCS (Posters & Demos).

  • Active AI Grid Member
  • Organizer of 1st and 2nd Workshop AI in Production at KI2024 and KI2025
  • Talk at AI Camp Nuremberg 2025: Not Just Another Prompt: The Higher Risks of Generative AI in Industrial Manufacturing
  • Participating in COST Action for Gender Balance in Informatics across Europe
  • Organizer Machine Learning Workshop 2. Oberfränkische Fachtagung KI
  • Talk at Collaboration Conference on Artificial Intelligence Prague: Artificial Intelligence in Industry and in Medicine

KMU-KI-Erfahrungszentrum Gewinner Innovationsort des Jahres 2025 (Innovator des Jahres)