conf.researchr.org / Eva-Maria Schön
Registered user since Fri 24 Feb 2023
Name:Eva-Maria Schön
Bio:
Eva-Maria Schön received her Ph.D. in Computer Science from the University of Seville (Spain) in 2017. She has been a full professor of business informatics at University of Applied Sciences Emden/Leer (Germany) since 2022. Previously, she was a full professor at HAW Hamburg for three years. For her, being a scientist means promoting agility in the workplace. Her research interests include agile product development, agile UX, requirements engineering, and GenAI in higher education. She also has many years of practical experience in digital product development and extensive experience in training and consulting for various companies in different business sectors.
Country:Germany
Affiliation:University of Applied Sciences Emden/Leer
Research interests: agile product development, agile UX, requirements engineering, GenAI in higher education
Contributions
2027
2026
XP
- Author of Teaching Agile Requirements Engineering: A Stakeholder Simulation with Generative AI within the Agile Training and Education-track
- Author of From AI Assistants to AI-Dev-Systems: A Three-Layer Model for Human-AI Collaboration in Agile Software Development within the WS: Human-AI Collab-track
- Academic Program Co-Chair in Organizing Committee
- Co-chair in Track Chairs within the Research Papers-track
- Organizing Committee of 2nd Agile Practice & Research (PR) Workshop within the Research Workshops -track
- Organizing Committee in Organizing Committee within the WS: Agile PR-track
2025
AgilePR
- Author of Towards a closer collaboration between practice and research in Agile Software Development – What we learnt; and what not? within the Towards a closer collaboration between practice and research in Agile Software Development – What we learnt; and what not? -track
- Committee Member in Organizing Committee within the Towards a closer collaboration between practice and research in Agile Software Development – What we learnt; and what not? -track