Qipeng Zhan

The paper introduces DG-UMAP, a supervised dimensionality reduction method that improves class structure preservation in biomedical data while maintaining local geometry.

GROTIA aligns multi-omics single-cell datasets using optimal transport and graph regularization, identifying key biological markers and enabling novel subpopulation discovery.

This paper introduces QOT, a method for efficiently computing sample-level distance matrices from single-cell omics data, showing improved accuracy and robustness over existing OT-based approaches.