Contact and Affiliations
- E-Mail:
- iryna.mozgova@uni-paderborn.de
- Phone:
- +49 5251 60-4573
- Office Address:
-
Pohlweg 47-49
33098 Paderborn - Room:
- P1.3.19
- E-Mail:
- iryna.mozgova@uni-paderborn.de
- Phone:
- +49 5251 60-4573
- Office Address:
-
Pohlweg 47-49
33098 Paderborn - Room:
- P1.3.19
About Iryna Mozgova
Curriculum Vitae
Since 2022: Professor of Data Management in Mechanical Engineering, Paderborn University
2017 - 2022: Team Leader "Methods of Product Development", Institute of Product Development, Leibniz University Hannover
2011 - 2017: Academic Councillor, Institute of Product Development, Leibniz University Hannover
2011 - 2011: Research Assistant, Institute of Product Development, Leibniz University Hannover
2009 - 2010: Research Assistant, Institute of Materials Science, Leibniz University Hannover
2002 - 2009: Docent, Department of Mathematical Support of Calculating Machines, Faculty of Applied Mathematics, Dnipropetrovsk National University, Ukraine
1997 - 2002: Research Assistant, Department of Mathematical Support of Calculating Machines, Faculty of Applied Mathematics, Dnepropetrovsk State University, Ukraine
2001: Doctorate under supervision of Prof. Dr.-Ing. habil. Oleksandr P. Prystavka, National Aviation University, Ukraine
1992 - 1997: Studies in Applied Mathematics, Dnipropetrovsk State University, Ukraine
Research
Latest Projects
- Automated rail transport as a backbone for sustainable, networked mobility in rural areas
- CRC 1368: Oxygen-free production - processes and local mechanisms in oxygen-free atmosphere for the development of sustainable production techniques and manufacturing processes
- CRC 1153 "Process chain for the production of hybrid high-performance components through tailored forming"
Publications
Latest Publications
A maturity based data management integration in engineering research projects
M.L. Wawer, L. Müller, J.B. Khaled, T. Stauß, J. Wurst, I. Mozgova, R. Lachmayer, Proceedings of the Design Society 5 (2025) 169–178.
Getting Things Done: How to Make Simulation Data FAIR and Ready to Reuse
L. Müller, M. Hinterthaner, E. Ortlieb, N. Mohnfeld, A.M. Schultz, J. Uhe, O. Koepler, I. Mozgova, in: IFIP Advances in Information and Communication Technology, Springer Nature Switzerland, Cham, 2025, pp. 140–150.
Fused Deposition Modeling and its Extension Through Metal-Filled Filaments as a Means of Self-Help for Individuals with Physical Disabilities
M. Ott, P. Jung, C. Bödger, I. Mozgova, R. Koch, T. Tröster, in: R. Lachmayer, S. Kaierle, M. Oel (Eds.), Innovative Produktentwicklung Durch Additive Fertigung, 2025, pp. 117–127.
Data Management in INF Projects of Collaborative Research Centres: Building Bridges Between Research, Infrastructure and Practice
O. Koepler, I. Mozgova, F. Nürnberger, C. Steinbeck, J. Pleiss, (2025) S. 23–39.
Strukturierte FDM-Plattformen: Aktuelle Lösungen und Herausforderungen in Informationsinfrastrukturprojekten
A.M. Schultz, I. Mozgova, O. Altun, O. Karras, O. Koepler, L. Müller, F. Nuenberger, D. Röwenstrunk, M.L. Wawer, Strukturierte FDM-Plattformen: Aktuelle Lösungen Und Herausforderungen in Informationsinfrastrukturprojekten, LibreCat University, 2025.
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Teaching
Current Courses
- Technische Darstellung (Übung)
- Technische Darstellung (Zentralübung)
- Technische Darstellung
- Technische Darstellung
- Standard Software Application Development (Exercise)
- Standard Software Application Development (Exercise)
- Standard Software Application Development
- Standard Software Application Development
- Projektseminar Rechnergestütztes Konstruieren und Planen
- Methoden des Qualitätsmanagements (Übung)
- Methoden des Qualitätsmanagements (Übung)
- Methoden des Qualitätsmanagements
- Methoden des Qualitätsmanagements
- Entwicklung nachhaltiger Produkte - ENTFÄLLT -
- Entwicklung nachhaltiger Produkte (Übung) - ENTFÄLLT -
- Data Science und Maschinelles Lernen (Übung)
- Data Science und Maschinelles Lernen
Scientific Engagement
Since 2021 | Member of the Research Data Alliance RDA
2020 - 2022 | Spokesperson, Quality assurance in Research Data Management processes and metrics for FAIR data, National Research Data Infrastructure for Engineering Sciences NDFI4Ing