Transforming Spatial Omics Data Into Biologically Actionable Insights
We develop computational and mathematical frameworks to understand how cells interact within complex tissue environments. Our mission is to bridge spatially resolved molecular measurements with mechanistic models of cellular communication and gene regulation, enabling quantitative interpretation of tissue organization in health and disease. We focus on spatial transcriptomics and multimodal imaging technologies to reconstruct cell states, intercellular signaling networks, and microenvironmental niches at single-cell resolution.
A central goal of the lab is to transform spatial omics data into biologically actionable insights. We design algorithms for cell segmentation refinement, transcript assignment correction, and integrated modeling of cell–cell communication and gene regulatory programs. Our work is motivated by inflammatory and autoimmune diseases, particularly pediatric gastrointestinal and liver disorders, where spatial tissue architecture plays a defining role in disease progression and therapeutic response.
