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Our group combines computational and experimental techniques to study the cellular organization of complex tissues, with a focus on determining the phenotypic diversity and clinical significance of tumor cell subsets. We have a particular interest in developing innovative data science tools that illuminate the cellular hierarchies and stromal elements that underlie tumor initiation, progression, and response to therapy. As part of this focus, we develop new algorithms to resolve cellular states and multicellular communities, tumor developmental hierarchies, and single-cell spatial relationships from genomic profiles of clinical biospecimens. Key results are further explored experimentally, both in our lab and through collaboration, with the goal of translating promising findings into the clinic. As a member of the Department of Biomedical Data Science and the Institute for Stem Cell Biology and Regenerative Medicine, and as an affiliate of graduate programs in Biomedical Informatics, Cancer Biology, and Immunology, we are also interested in the development of impactful biomedical data science tools in areas beyond our immediate research focus, including developmental biology, regenerative medicine, and systems immunology.