BIOMEDICAL IMAGES ENCODE TRACES OF AN UNDERLYING PHENOTYPE, WE ARE LEARNING TO TRANSLATE THEM INTO MATHEMATICAL BIOMARKERS.
BIOMEDICAL IMAGES ENCODE TRACES OF AN UNDERLYING PHENOTYPE, WE ARE LEARNING TO TRANSLATE THEM INTO MATHEMATICAL BIOMARKERS.
Our lab focuses on the theory, development, and application of computational / mathematical oncology. We interrogate cancer at different length-scales of its biological organization via high-performance scientific computing, multiscale mathematical modeling, advanced imaging technology, and the applied analysis of stochastic partial differential equations. Current research interests include tumor topology, cellular dynamics, immune microenvironment, drivers of radiation resistance and immune dysregulation, molecular insight into tissue heterogeneity, and biologically-guided adaptative treatment strategies.
Our lab focuses on the theory, development, and application of computational / mathematical oncology. We interrogate cancer at different length-scales of its biological organization via high-performance scientific computing, multiscale mathematical modeling, advanced imaging technology, and the applied analysis of stochastic partial differential equations. Current research interests include tumor topology, cellular dynamics, immune microenvironment, drivers of radiation resistance and immune dysregulation, molecular insight into tissue heterogeneity, and biologically-guided adaptative treatment strategies.
Funding
Funding