Beijing Academy of Artificial Intelligence

Latent diffusion model that backmaps coarse-grained protein structures to all-atom detail, with bond geometry learned into the latent space.

Protein-ligand binding model that embeds ligands, pockets, and sequences in hyperbolic space, unifying virtual screening and affinity ranking.

Structure-based virtual screening model that scores ligands against apo and predicted pockets, lifting blind-apo EF1% on DUD-E from 11.75 to 37.19.

Generative diffusion model that samples biomolecular conformational ensembles for proteins, RNA, and ligands in hours instead of millisecond-scale MD.

Multimodal large language model for 3D medical imaging that handles report generation, visual question answering, and segmentation on CT volumes.

Promptable 3D foundation model for volumetric CT segmentation, covering over 200 anatomical categories through point, box, and free-text prompts.

Structure prediction for protein, RNA, and protein-RNA complexes in one AlphaFold2-derived framework that accepts MSA or language model encoders.