Charité – Universitätsmedizin Berlin

Medical imaging foundation model unifying pathology and radiology, serving classification and segmentation on 2D, 3D and gigapixel inputs.

Open-weights pathology foundation models pairing a 1.1B-parameter ViT-g/8 tile encoder with distilled 86M and 22M variants for H&E histology.

Bidirectional DNA foundation model with a Mamba-attention-mixture-of-experts design, reading 1 million base pairs at single-nucleotide resolution.

Fragment-ion intensity prediction for cross-linked peptides, covering cleavable DSSO and DSBU chemistries alongside non-cleavable DSS and BS3.

Diffusion autoencoder framework that morphs H&E tiles until a pathology classifier flips, exposing the morphology behind the prediction.

Multimodal contrastive model aligning clinical EEG with free-text reports, enabling zero-shot EEG classification from natural-language prompts.

Self-supervised pathology foundation model with a 300M-parameter vision transformer tile encoder, trained on a multi-stain whole-slide image corpus.