Rohit Bhargava

Rohit Bhargava developed infrared spectral imaging and AI-based digital pathology tools for quantitative spatial profiling of CAF subtypes within the tumor microenvironment, enabling clinical-grade assessment of stromal composition as a predictive biomarker for therapy response without requiring immunohistochemistry. His computational analyses of tumor-stroma interface architecture demonstrated that CAF spatial organization patterns predict patient outcomes more accurately than CAF abundance alone, revealing that CAF barrier formation around tumor nests correlates with immunotherapy resistance. He develops clinical decision support tools incorporating stromal spatial features for personalized cancer therapy selection.