Alexander Chan Chi Huang

The paper develops MAESTRO, a self-supervised deep learning framework to transform immune profiles into embeddings capturing immune health, enabling clinical prediction and precision immunotherapy.

The paper identifies a lymphatic circuit that sustains stem-like CD8+ T cells by recycling tumor-experienced effector T cells, enhancing immune surveillance and ICB response.

HistoSweep improves tissue quality control in gigapixel images by removing artifacts and preserving biologically relevant structures, enhancing analysis accuracy in digital pathology and spatial omics.

The paper develops a CRISPRi platform to annotate functional enhancers in human T cells, identifying novel CREs and their regulatory roles in immune responses.

The paper identifies Treg-CD8 T cell interactions in the sentinel lymph node as predictors of melanoma recurrence in Stage II patients.

This study identifies microbiome-derived protein biomarkers for predicting immunotherapy response and toxicity in melanoma without relying on taxonomic classification.

The paper identifies TR-TEX cells as distinct from TRM cells, showing they have unique transcriptional regulation and respond differently to PD-1 inhibition.

This study develops DR5-targeted CAR-T cells that kill solid tumors and MDSCs, enhance CD8+ T cell activity, and show minimal toxicity in preclinical models.