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BioDr. Lund was born in Duluth, MN and attended Harvard College and Harvard Medical School. He received his general surgical training at the MGH in Boston, and his pediatric surgical training at Boston Children's Hospital. His initial career was spent as a trauma, transplant and general pediatric surgeon at Boston Children's. In 1999, he became Surgeon-in-Chief of the University of Wisconsin Children's Hospital in in Madison, and in 2001 became Chair of General Surgery at the University of Wisconsin-Madison. In 2011, he became Executive Vice President of the Phoenix Children's Medical Group and Surgeon-in-Chief at Phoenix Children's Hospital. Dr. Lund joined the Stanford faculty in Pediatric Surgery and as Associate Dean of the Faculty in Pediatrics and Obstetrics (Clinical Affairs) as well as Chief Medical Officer at Lucile Packard Children's Hospital in March, 2015. In March of 2018 and through January of 2019, Dr. Lund served as interim President and CEO of Lucile Packard Children's Hospital.

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Denny Lund

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.

Holly Lung

Biostatistician 1, Pediatrics - Adolescent Medicine

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