Lulu Shang
Assistant Professor
The University of Texas MD Anderson Cancer Center
Department of Biostatistics
My research program centers on developing innovative statistical and computational methods for spatial biology, single-cell genomics, and integrative multi-omics. I design scalable, interpretable, and data-driven models that capture complex molecular, cellular, and spatial organization in human tissues, with the broader goal of advancing our understanding of disease mechanisms across diverse biological systems. By integrating statistical modeling, deep learning, and high-dimensional genomic profiling, my lab builds tools that enable quantitative characterization of tissue architecture, cellular heterogeneity, and gene regulatory processes. We work closely with experimental and clinical collaborators to ensure that our methods generate biologically meaningful and clinically actionable insights, including applications in cancer when improved spatial and molecular resolution can inform diagnosis, prognosis, and therapeutic strategies. Ultimately, my research aims to create broadly applicable computational frameworks that strengthen the bridge between modern genomics technologies and biomedical discovery.
Education & Training
PhD, University of Michigan, 2023