Tejaswini Medi

Researcher

University of Mannheim

B6, 28–29, Room C 001, 68159, Mannheim

Email: tejaswini.medimail-uni-mannheim.de

Webpage: tejaswinimedi.github.io

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Research Interests

Robustness and Fairness of Deep Learning Models
Image and 3D Generation
Representation Learning

Publications

Tejaswini Medi, Julia Grabinski, Margret Keuper, “Towards Class-wise Robustness Analysis” accepted at OOD Generalization in Computer Vision Workshop, ICCV 2023.Tejaswini Medi, Jawad Tayyub, Muhammad Sarmad, Frank Lindseth, Margret Keuper, “FullFormer: Generating Shapes Inside Shapes”, accepted at DAGM German Conference on Pattern Recognition, Heidelberg, 2023. Tejaswini Medi, Steffen Jung, Margret Keuper, " FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training”, accepted at Proceedings of the Winter Conference on Applications of Computer Vision (WACV), 2025

Teaching

Teaching Assistant

Generative Computer Vision Models ( FSS 2024, FSS 2025)
Machine Learning ( HWS 2024)
Seminar Organization (AI Safety & Robustness) ( FSS 2025)
Seminar Supervision ( HWS 2024 – FSS 2025)

Community Participation

Active Reviewer for TPAMI, CVPR and NeurIPS Conferences

Dr. Jan Delcker

Postdoctoral Researcher at the Chair of Economic and Business Education, Learning, Design and Technology

delckeruni-mannheim.de

Website

Main fields of research

Teaching and learning with digital technologies
Digitalization in school development
School development models
Educational Data Literacy

Curriculum vitae

2022	Dr. rer. pol. (PhD), Phd thesis “Transforming Vocational Schools – Digitalization in School Development“
Since 2015	University of Mannheim, Research Assistant at the Chair for Economic and Business Education – Learning, Design & Technology
2012–2015	Hochschule Mannheim, M.A. Social Work, Master thesis “Pfandsammler“
2008–2012	Hochschule Mannheim, B.A. Social Work, Bachelor thesis “Computerspiele als Anlass zur medienpädagogischen Arbeit in Familien“

Selected publications

Delcker, J., Heil, J. and Ifenthaler, D. (2025). Evidence-based development of an instrument for the assessment of teachers’ self-perceptions of their artificial intelligence competence. Educational Technology Research and Development : ET R & D, 73, 115–133.
Delcker, J., Heil, J., Ifenthaler, D., Seufert, S. and Spirgi, L. (2024). First-year students AI-competence as a predictor for intended and de facto use of AI-tools for supporting learning processes in higher education. International Journal of Educational Technology in Higher Education, 21, 1–13.
Delcker, J., Heil, J., Ifenthaler, D., Seufert, S. and Spirgi, L. (2024). First-year students' usage of and attitudes towards mindless and mindful AI-technology. In Artificial intelligence for supporting human cognition and exploratory learning in the digital age (S. 25–40). Cham, Switzerland: Springer.
Heil, J., Delcker, J., Ifenthaler, D., Seufert, S. and Spirgi, L. (2024). KI-Kompetenz zu Studienbeginn als Prädiktor für die Nutzung von KI-Werkzeugen zur Unterstützung von Lernprozessen. Informatik-Spektrum, 47, 51–59.
Seufert, S., Spirgi, L., Delcker, J., Heil, J. and Ifenthaler, D. (2024). Umgang mit KI-Robotern: maschinelle Übersetzer, Textgeneratoren, Chatbots & Co – Eine empirische Studie bei Erstsemester-Studierenden. Empirische Pädagogik : EP, 38, 47–72.
Delcker, J. (2023). Digitalisation in the curricula of vocational schools: text mining as an instrument of curricula analysis. Technology, Knowledge and Learning, 28, 999-1014.
Delcker, J. (2022). Transforming vocational schools – digitalisation in school development. Dissertation. Mannheim.
Delcker, J. and Ifenthaler, D. (2022). Digital distance learning and the transformation of vocational schools from a qualitative perspective. Frontiers in Education, 7, 1–15.
Delcker, J. and Ifenthaler, D. (2022). Distance learning and the influence of schools' organizational characteristics on the students perceived learning success. In Global perspectives on educational innovations for emergency situations (S. 241–250). Cham: Springer International Publishing.