Stanford University
Showing 371-380 of 630 Results
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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 spatial omics and computational methods to measure, model, and predict 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
Associate 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 whose research develops and evaluates machine learning systems that combine medical imaging, electronic health record data, and clinical outcomes. His current work concerns medical foundation models, agentic clinical systems, and the prospective evaluation of AI in real clinical workflows. He joined the Stanford faculty in 2014 in the Department of Radiology, serving as Assistant Professor and then Associate Professor through 2021 while leading a dedicated pediatric interventional radiology service. He co-founded and co-directed the Stanford Center for Artificial Intelligence in Medicine and Imaging. He remains Adjunct Professor of Biomedical Data Science at Stanford, where he co-teaches Generative AI and Medicine, and holds a part-time clinical appointment at UCSF. He serves as an independent board director and scientific advisor to medical technology, health system, and life science organizations. In industry, Dr. Lungren served as Chief Scientific Officer for Health and Life Sciences and as AI Technical Advisor in the Office of the CTO at Microsoft.
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 -
Liqun Luo
Ann and Bill Swindells Professor and Professor, by courtesy, of Neurobiology
Current Research and Scholarly InterestsWe study how neurons are organized into specialized circuits to perform specific functions and how these circuits are assembled during development. We have developed molecular-genetic and viral tools, and are combining them with transcriptomic, proteomic, physiological, and behavioral approaches to study these problems. Topics include: 1) assembly of the fly olfactory circuit; 2) assembly of neural circuits in the mouse brain; 3) organization and function of neural circuits; 4) Tool development.
