I'm a Ph.D. student at TU Vienna, working at the intersection of AI and biology with a focus on computer vision for single-cell and multiplex tissue imaging. In the Taschner-Mandl Lab, I build methods that help turn complex microscopy data into reliable, interpretable, and actionable biological insights.
My research centers on weakly- and self-/unsupervised learning for high-dimensional imaging data, with particular emphasis on:
- Representation learning and robust feature extraction
- Uncertainty estimation and failure-case awareness
- Interpretability and biologically meaningful model behavior
I work across multiple imaging modalities, including Immunofluorescence, FISH, and multiplex platforms such as IMC, CODEX, and MIBI.
Alongside research, I’m also a scientific illustrator. I care deeply about making complex ideas understandable—not just correct. I design figures, posters, and visual stories, and I regularly give lectures and hands-on workshops on scientific illustration: how to build clear visual narratives, craft publication-ready figures, and communicate results effectively to both expert and non-expert audiences.
A selection of posters and materials from international conferences:
- Best Poster — MICCAI COMPAYL 2025
- Best Poster — MICCAI UNSURE 2024
- Poster — ESSB
- Poster — AI & Biology
I also presented my work at TEDxAI Vienna 2025. If you want to try the interactive demo:
If you’d like to connect or collaborate, feel free to reach out on LinkedIn.