Carnegie Mellon University
A private research university in Pittsburgh with deep roots in AI and robotics, applying them across genomics, drug design, and clinical signals.
Labs & Groups (1)
Models (11)
Hybrid framework that predicts ribosome location profiles from mRNA sequence alone, pairing a structure-aware TASEP simulation with a Mamba polisher.
Protein foundation model for de novo enzyme design that co-designs sequence and 3D structure under small-molecule ligand guidance, at 730M parameters.
EEG foundation model pretrained by spectrogram reconstruction that improves online directional motor-imagery brain-computer interface control.
Tokenizer-free genomic foundation model that adaptively chunks raw nucleotides, enabling zero-shot variant fitness and gene essentiality prediction.
Structure-based drug design model that unifies de novo generation, docking, conformer generation, and pharmacophore conditioning via flow matching.
Spatial transcriptomics language model that reads tissue as spatial sentences to simulate cell profiles and run in silico perturbations.
Generative framework that reconstructs missing spatial transcriptomics regions by jointly predicting cell locations, cell types, and gene expression.
PRISM
Carnegie Mellon University / Mohamed bin Zayed University of Artificial Intelligence / Intel
Released October 13, 2025
Retrieval-augmented inverse folding model that fuses structural motif retrieval with a hybrid attention decoder to design sequences for a backbone.
Multimodal large language model that interprets 12-lead electrocardiogram images, answering open-ended clinical questions and generating ECG reports.
Transformer-based single particle tracker for fluorescence microscopy, using multi-hypothesis attention to link particles at low SNR and high density.
Multi-modal self-supervised transformer for regulatory genomics, pre-trained on DNA sequence together with transcription factor binding matrices.