School of Medicine
Showing 6,831-6,840 of 12,920 Results
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Emma Lundberg
Associate Professor of Bioengineering and of Pathology
BioDr. Emma Lundberg is an Associate Professor of Bioengineering and Pathology at Stanford University and serves at the Director of the Cell Atlas of the Human Protein Atlas initiative in Sweden, where she is also Professor at KTH Royal Institute of Technology. At the intersection of bioimaging, proteomics, and artificial intelligence, her research aims to define the spatiotemporal organization of the human proteome at both cellular and subcellular level. Dr. Lundberg aims to develop integrated models of human cells to elucidate how variations in protein localization patterns influence cellular function, ultimately enabling the simulation of cell behavior and a systems-level understanding of how biological information is spatially encoded. The Lundberg Lab is responsible for creating the Subcellular Atlas of the Human Protein Atlas database (https://www.proteinatlas.org/). Dr. Lundberg is dedicated to building virtual cell models to simulate cell behavior, and is passionate about engaging the public in her work through citizen science games and computational challenges.
Dr. Lundberg holds a Master’s degree in Bioengineering and a PhD in Biotechnology from KTH Royal Institute of Technology in Sweden. She has served as Secretary General of the Human Proteome Organization, and is actively involved in advisory roles for numerous open-access databases and cell mapping efforts such as the CZI AI Virtual Cell, Human Cell Atlas consortium, UniProt db, Reactome db, Human Proteome Project and various pharma and biotech companies. As a token of her leadership skills and advocate for open science, she was twice recognized as top 10 under 40 for future leaders in biopharma and omics. -
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 -
Mitchell R. Lunn
Associate Professor of Medicine (Nephrology) and, by courtesy, of Epidemiology and Population Health
Current Research and Scholarly InterestsLGBTQIA+ health
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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.
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Ruben Y. Luo
Assistant Professor of Pathology
Current Research and Scholarly InterestsApply top-down mass spectrometry and label-free immunoassay to the study and utilization of biomarker proteoforms in clinical diagnosis.
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Xiangde Luo
Postdoctoral Scholar, Radiation Physics
BioXiangde Luo is a postdoctoral researcher in Professor Ruijiang Li’s lab at Stanford Medicine, where he specializes in computational pathology. His work centers on developing AI‑driven methods for imaging biomarker discovery and precision oncology. Previously, he has developed some deep learning models to enable annotation‑efficient learning and advance biomedical image analysis. For a comprehensive overview of my research, please visit my Google Scholar profile: https://scholar.google.com/citations?hl=en&user=dD4HLS4AAAAJ. If you’d like to learn more or discuss potential collaborations, please don’t hesitate to get in touch.
