School of Medicine
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Assistant Professor of Medicine (Oncology)
Current Research and Scholarly InterestsMy research is on the translational application of next-generation sequencing technologies to breast cancer care: (1) the value of hereditary cancer genetic panel testing in clinical practice, (2) the mechanisms by which inherited genetic variants lead to breast cancer development, and (3) the analysis of somatic tumor sequencing data to inform understanding of breast tumorigenesis, metastasis, and development of resistance in response to therapeutics.
Michelle M. Chen, MD, MHS
Assistant Professor of Otolaryngology - Head & Neck Surgery (OHNS)
BioDr. Chen is a fellowship-trained head and neck surgical oncologist with a board certification in otolaryngology and a clinical assistant professor with the Stanford School of Medicine Department of Otolaryngology.
Her practice focuses on the treatment of cancers that affect the head and neck. She has received additional training in microvascular reconstruction and transoral robotic surgery.
Dr. Chen has an active lab involved in head and neck cancer health services research and her work has appeared in numerous journals, including The Journal of the American Medical Association, Cancer, Journal of the National Cancer Institute, and Journal of Clinical Oncology. She has also authored chapters in textbooks on head and neck cancer treatment.
Dr. Chen is a member of the American Academy of Otolaryngology—Head & Neck Surgery (AAOHNS) and the American Head & Neck Society.
Assistant Professor of Psychiatry and Behavioral Sciences (Child and Adolescent Psychiatry and Child Development)
Current Research and Scholarly InterestsDr. Cosgrove studies putative roles for life and family stress as well as inflammatory and neurotrophic pathways in the etiology and development of mood disorders across the life span.
RZ Cao Professor, Professor of Genetics and of Biomedical Data Science
Current Research and Scholarly InterestsThe Curtis laboratory for Cancer Computational and Systems Biology is focused on the development and application of innovative experimental, computational, and analytical approaches to improve the diagnosis, treatment, and early detection of cancer.