School of Medicine
Showing 361-370 of 623 Results
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Alarice Cheng-Yi Lowe
Associate Professor of Pathology
BioDr. Lowe joined the School of Medicine faculty in 2019. She received her undergraduate degree in Biology from MIT and her medical degree at UCSD, prior to residency and cytology fellowship at UCLA. In 2011, she joined the faculty at Brigham and Women's Hospital where she developed a research focus on Circulating Tumor Cells (CTCs) and the application of new technology to improve clinical and molecular diagnostics. Clinically, her interests focus on Cytopathology and Genitourinary Pathology.
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Anson Lowe
Associate Professor of Medicine (Gastroenterology and Hepatology), Emeritus
Current Research and Scholarly InterestsThe laboratory is focused on the relationship between injury, wound healing, and cancer. Esophageal, gastric, and pancreatic cancers are a focus. We are particularly interested in the regulation of cell signaling by EGFR, the EGF receptor. In addition to cancer pathogenesis, active projects include the development of new diagnostic assays and drugs.
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Robert Lowsky
Professor of Medicine (Blood and Marrow Transplantation and Cellular Therapy)
Current Research and Scholarly InterestsDr. Lowsky's research is focused on understanding the role of regulatory T cells in the prevention of GVHD and in promoting immune tolerance following organ transplantation.
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Bingwei Lu
Professor of Pathology
Current Research and Scholarly InterestsWe are interested in understanding how neural stem cells balance their self-renewal and differentiation and how deregulation of this process can result in brain tumor. We are also interested in mechanisms of neurodegeneration in Alzheimers and Parkinsons diseases. We are using both Drosophila and mammalian models to address these fundamental questions.
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Lu,Guolan
Assistant Professor of Urology
Current Research and Scholarly InterestsThe Lu Lab develops and integrates AI, spatial multi-omics, and advanced imaging to understand and model how cells, tissues, and therapeutic agents interact in their native spatial context, and how these interactions drive disease progression and treatment response.
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Sydney X. Lu
Assistant Professor of Medicine (Hematology)
BioSydney Lu is an assistant professor and physician-scientist in the Division of Hematology, Department of Medicine with a broad interest in both normal and abnormal RNA processing in the context of normal physiology and disease states. The laboratory studies translational questions regarding the mechanistic basis of RNA processing abnormalities in malignant blood disorders, their implications for leukemogenesis and cancer biology, as well as resultant therapeutic opportunities.
As a physician, Sydney’s group is particularly focused on dissecting RNA processing abnormalities in primary patient samples and disease-relevant preclinical model systems. Lab members employ a variety of ‘wet-lab’ and computational approaches to study transcriptome abnormalities in (1) states of immune dysfunction, (2) myeloid blood cancers such as myelodysplastic syndromes and acute myeloid leukemia, and (3) lymphoid blood cancers such as chronic lymphocytic leukemia. Additional projects are focused on novel therapeutics, including multiple targeted agents which modulate RNA processing, for the selective treatment of these diseases.
Sydney’s research is/has been supposed by grant funding from the National Cancer Institute, Parker Institute for Cancer Immunotherapy, Leukemia & Lymphoma Society, Aplastic Anemia & Myelodysplastic Syndromes International Foundation, the American Society for Clinical Oncology, the American Society of Hematology, the American Association for Cancer Research, the Paula and Rodger Riney Foundation, the Doris Duke Charitable Foundation, The Gabrielles Angel Foundation for Cancer Research, and the Stanford Cancer Institute. -
Ying Lu
Professor of Biomedical Data Science and, by courtesy, of Epidemiology
Current Research and Scholarly InterestsBiostatistics, clinical trials, statistical evaluation of medical diagnostic tests, radiology, osteoporosis, meta-analysis, medical decision making
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Natalie Shaubie Lui
Assistant Professor of Cardiothoracic Surgery (Thoracic Surgery)
BioDr. Lui studied physics as an undergraduate at Harvard before attending medical school at Johns Hopkins. She completed a general surgery residency at the University of California San Francisco, which included two years of research in the UCSF Thoracic Oncology Laboratory and completion of a Master in Advanced Studies in clinical research. Dr. Lui went on to hold a fellowship in Thoracic Surgery at Massachusetts General Hospital, during which she participated in visiting rotations at Memorial Sloan Kettering and the Mayo Clinic.
Dr. Lui’s surgical practice consists of general thoracic surgery with a focus on thoracic oncology and robotic thoracic surgery. Her research interests include intraoperative molecular imaging for lung cancer localization, increasing rates of lung cancer screening, and using artificial intelligence to predict lung cancer recurrence. She is the recipient of the Donald B. Doty Educational Award in 2019 from the Western Thoracic Surgical Association, the Dwight C. McGoon Award for teaching from the Thoracic Surgery Residents Association in 2020, and the Carolyn E. Reed Traveling Fellowship from the Thoracic Surgery Foundation and Women in Thoracic Surgery in 2022. -
Matthew Lungren
Adjunct Professor, Biomedical Data Science
BioDr. Matthew Lungren is a physician-scientist and AI leader whose work has helped shape modern multimodal healthcare AI from early research through large-scale deployment. He joined Stanford University in 2014 as clinical research faculty, where he led a fully dedicated pediatric interventional radiology clinical service and established an NIH- and industry-supported clinical AI research program that helped catalyze what became the Stanford Center for AI in Medicine & Imaging. He remains an Adjunct Professor of Biomedical Data Science at Stanford and also holds a part-time clinical appointment at UCSF.
Dr. Lungren has authored more than 200 peer-reviewed publications with more than 35,000 citations, and he has taught more than 100,000 learners through AI-in-healthcare courses across platforms including Coursera and LinkedIn Learning. His broader contributions include advancing multimodal imaging-plus-EHR approaches, open-sourcing AI-ready medical imaging datasets and models, and serving in national leadership roles across the radiology AI community. After a sabbatical in 2021, he transitioned from academia to industry and joined Microsoft, where he served in senior leadership roles including Chief Scientific Officer for Microsoft Health & Life Sciences. At Microsoft, he founded and led cross-company teams that shipped multimodal healthcare foundation models and agentic, auditable generative AI workflows into production, including healthcare agent orchestration capabilities and major EHR partnerships, and led the health and life sciences partnerships with OpenAI.
Dr. Lungren is also a top rated instructor leading AI in Healthcare courses designed especially for learners with non-technical backgrounds:
Stanford/Coursera: https://www.coursera.org/learn/fundamental-machine-learning-healthcare
LinkedIn Learning: https://www.linkedin.com/learning/an-introduction-to-how-generative-ai-will-transform-healthcare
