The Machine Learning team of DaMBi explores both fundamental ML research as well as applications in bio-informatics.

In the realm of fundamental research, we focus mostly on explainability and adversarial robustness, striving to enhance the understanding of ML models and their shortcomings.

On the applied front, we tackle exciting challenges like cell segmentation, spatial transcriptomics, and imaging flow cytometry, leveraging ML techniques to unlock new insights and advancements in these domains.