- Composition Counts: A Machine Learning View on Immunothrombosis using Quantitative Phase Imaging. Machine Learning for Healthcare Conference, 2023 mehr… BibTeX
- Platelet aggregates detected using quantitative phase imaging associate with COVID-19 severity. Commun Med (3), 2023, 161 mehr… BibTeX Volltext ( DOI )
- Measurement of Platelet Aggregation in Ageing Samples and After in-Vitro Activation. Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, SCITEPRESS - Science and Technology Publications, 2023 mehr… BibTeX Volltext ( DOI )
David Fresacher, M.Sc.
Technische Universität München
Lehrstuhl für Datenverarbeitung
Arcisstraße 21
80333 München
Tel.: +49 (0)89 289 23623
Fax.: +49 (0)89 289 23600
E-Mail: david.fresacher@tum.de
Büro: Z943
Kontakt
Wenn Sie Fragen zu Workshops oder Lehrveranstaltungen haben, schreiben Sie an folgende Adressen.
- Komputer & Creativität: kc.ldv(at)xcit.tum.de
- 3D-Druck: 3d.ldv(at)xcit.tum.de
- Python: py.ldv(at)xcit.tum.de
Forschungsschwerpunkte
Generative Models and Computer-Aided Design:
Exploring the use of generative AI to create interpretable and modifiable 3D models by synthesizing in a domain-specific language, improving readability and modifiability compared to traditional voxel-based methods.
Human-AI Interaction:
Developing effective interfaces to facilitate iterative co-creation workflows, enabling collaboration between human designers and AI systems.
Trust and Transparency in AI:
Ensuring trustworthiness in AI systems through explainable and transparent processes, particularly in the context of CAD-based generative design.
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