His areas of research include image analysis, computational phenotyping, natural language processing, and multi-modal predictive disease models, with a preference for problems that have a clear pathway to clinical translation. Most projects share the goal of integrating radiology, pathology, and molecular features to further understanding of disease through the discovery of predictive computational phenotypes that may be used for risk stratification, treatment selection, and response monitoring. His lab also serves as a resource for department physicians, fellows, and residents who wish to incorporate machine learning/data science techniques into their research.