Sriram P. Chockalingam

scSAGA improves multimodal single-cell data integration by preserving geometry and scaling efficiently, outperforming existing methods on various datasets.

SCEMENT integrates large-scale single cell RNA-seq data efficiently, outperforming existing methods in speed and memory usage while preserving quantitative gene expression information.

FastDE accelerates differential gene expression analysis in single-cell data by 50X, replicating age and gender effects on immune cell differentiation in PBMC atlases.

MCPNet constructs high-quality gene networks efficiently and scalably using a novel maximum-capacity-path metric, outperforming existing methods in speed and accuracy.