University of Southern California

Protein perturbation model conditioning substitution-effect prediction on a learned protein-level regime coordinate over 202 million sequences.

Genomic foundation model on a Mamba, attention, and mixture-of-experts backbone, with 1M-token context for variant scoring and regulatory DNA design.

Antibody CDR design model fusing diffusion with a GFlowNet objective so binding energy is optimized during training rather than by post-hoc RL.

Functional ultrasound reconstruction with neural operators, rebuilding power Doppler brain images from 10-15% of the usual compounded frames.

Hi-C resolution enhancement model combining a U²-Net with self-attention to recover TAD boundaries and chromatin loops from sparse contact maps.

Medical vision-language model trained with reinforcement learning for generalizable reasoning across eight imaging modalities and five question types.

Promptable 3D segmentation for particle picking in cryo-electron tomography, conditioned on a reference subtomogram to detect any target complex.

Metagenomic foundation model pretrained on 1.5 trillion base pairs of wastewater DNA and RNA for pathogen detection and biosurveillance.

De novo peptide sequencing model that retrieves a similar peptide-spectrum match from a database and fuses it into transformer decoding.

EEG foundation model that pairs a convolutional encoder with a GPT backbone, pretrained by masked-segment reconstruction for low-data BCI decoding.