Arvind Rao

Arvind Rao, Ph.D.

Associate Professor, Department of Computational Medicine and Bioinformatics
MIDAS, Radiation Oncology


Dr. Rao works at the intersection of genomics  and  image informatics, across biological scale (cells, tissue and organ). He is interested in developing multi-modal decision algorithms that link and integrate various measurements (imaging, genomics etc) to characterize disease. His algorithms for phenotypic measurements encompass data from 2D/3D microscopy, radiology and histopathology. He is also interested in methodological aspects of genomic analysis and image assessment. In the context of these investigations, Dr. Rao collaborates with clinicians, biologists, engineers and data scientists.

Research Interests

My graduate work in bioinformatics aimed to develop a framework that identifies tissue‐specific enhancers by integrating multi‐modal genomic (gene expression, methylation and interaction) data. As a postdoctoral fellow in Carnegie Mellon University, I obtained training in data mining methods for image analysis. At the MD Anderson Cancer Center previously and now at the University of Michigan, I build methods to analyze the relationship between image‐derived phenotypic attributes and genotypic attributes for cancer patients. Such image data is obtained from multiple modalities including, single cell high content microscopy, H&E whole slide data, immunohistochemistry, molecular imaging and radiology. My research aims to develop quantitative frameworks to build an integrative framework to analyze such image data and correlate them with genetic features like expression, mutation or copy number; and further, to integrate these diverse modalities to develop decision algorithms for prognosis and treatment selection. Some details below.