Transformer-based pipeline for cell type classification across multimodal single-cell and spatial omics datasets.
- Extended a foundation transformer model pre-trained on 500K+ cells for supervised classification.
- Built training, fine-tuning, and inference scripts with configurable model sizes/datasets.
- Automated reproducible GPU experiments using Bash job scripts on remote instances.
Code is private due to research constraints associated with this project.