Lavinia Goldermann, M.Sc. RWTH
Contact
Research Assisstent
Tel. +49 241 80 - 21142
Fax +49 241 80 22150
Email: goldermann[at]embedded[dot]rwth-aachen[dot]de
Addresse: Ahornstr. 55, 52074 Aachen, Germany
Office: 2325
Research
As part of my research work, I deal with the data quality of intensive care data. In particular, my focus is on intensive care data that is collected using unobtrusive measurement methods. With the help of AI methods and xAI methods, additional statements about data quality can be made.
Theses currently supervised
- Bachelor thesis - Generation of annotated ICU data with AI-based methods
- Bachelor thesis - Identification of anomaly classes in intensive care time series data by clustering-based analysis
Teaching
Publications
Publikations-Export
- [GRB+24]PDFBIB
- Goldermann, L., Rakel, S., Buglowski, M., Mokhtarian, A., Kampmann, A., Janß, A., Yilmaz, O., Beger, F., Walter, M., Leonhardt, S., Kowalewski, S., and Stollenwerk, A., "Designing the user interface of a ventilator under the constraints of a pandemic", Automatisierungstechnik, vol. 72, iss. 5, pp. 484-495, 2024
Designing the user interface of a ventilator under the constraints of a pandemic
Bibtex entry :
@article { GRB+24, author = { Goldermann, Lavinia and Rakel, Stefan and Buglowski, Mateusz and Mokhtarian, Armin and Kampmann, Alexandru and Jan{\ss}, Armin and Yilmaz, Okan and Beger, Frank and Walter, Marian and Leonhardt, Steffen and Kowalewski, Stefan and Stollenwerk, André }, title = { Designing the user interface of a ventilator under the constraints of a pandemic }, journal = { Automatisierungstechnik }, publisher = { De Gruyter }, pages = { 484-495 }, volume = { 72 }, number = { 5 }, year = { 2024 }, address = { Berlin }, issn = { 0178-2312 }, doi = { 10.1515/auto-2023-0205 }, typ = { PUB:(DE-HGF)16 }, reportid = { RWTH-2024-04857 }, cin = { 122810 / 611010 / 419410 / 120000 }, }
RWTH Aachen University - Chair of Computer Science 11 - Ahornstr. 55 - 52074 Aachen - Germany