About me

My work and research focus on making ML usable for practitioners, especially in the field of Biology. In my current role as a Ph.D. candidate, I utilize CNNs and other ML-based approaches to address limitations in widely used fluorescence microscopy. Some of my work includes:

• aisegcell: An implementation of U-Net to segment cell nuclei in transmitted light microscopy images.
• napari-aisegcell: A graphical user interface for the aisegcell package available via napari.
• model-runner: CLI to submit a hyper-parameter optimization (i.e. grid search) via LSF or slurm
• torch-model-zoo: A (soon to be) collection of PyTorch models (incl. Vanilla ViT).