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Aaron Newman is an Associate Professor in the Department of Biomedical Data Science at Stanford University. His research focuses on the intersection of computational and experimental techniques to study the cellular organization of complex tissues, with particular emphasis on the cellular diversity and clinical relevance of tumor cell subsets within their microenvironments. Newman is dedicated to developing innovative data science tools aimed at elucidating the cellular hierarchies and stromal elements that drive tumor initiation, progression, and response to therapy. His work often involves the creation of new algorithms to resolve distinct cellular states within multicellular communities and analyze single-cell spatial relationships of genomic profiles in clinical biospecimens. He holds various leadership roles and has been recognized with multiple awards for his contributions to the field, including the 3rd Annual Daisy Ho Memorial Award and the K99/R00 Pathway Independence Award from NIH/NCI. Newman is also an advocate for impactful biomedical data science tools that enhance research in developmental biology, regenerative medicine, and systems immunology.
The Computer Science department emphasizes research potential. GRE General is currently optional but recommended for some tracks.