School of Medicine
Showing 1-20 of 31 Results
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Corinne Beck
Program Manager, Center for Cancer Systems Biology (CCSB), Biomedical Data Science
Current Role at StanfordProgram Manager
Stanford Center for Cancer Systems Biology (CCSB)
Plevritis Lab
Department of Biomedical Data Science (DBDS)
School of Medicine | Stanford University -
Michelle Whirl-Carrillo
Principal Investigator and Director, PharmGKB, Biomedical Data Science
Current Role at StanfordPrincipal Investigator and Director, PharmGKB
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Francisco M. De La Vega
Adjunct Professor, Biomedical Data Science
BioFrancisco De La Vega is a distinguished geneticist and computational biologist, and an experienced technical executive, widely recognized for his expertise in clinical and population genomics, and bioinformatics. Currently serving as the Vice President of Hereditary Disease at Tempus Labs, Francisco is spearheading the development of comprehensive germline genetic tests and conducting innovative research into racial disparities in cancer leveraging Tempus’ multimodal Real-World Data. His work focuses on uncovering the connections between genetic ancestry and cancer genome mutational profiles that may help explain the differences in cancer incidence and outcomes across races and ethnicities. In addition to his role at Tempus Labs, Francisco is an Adjunct Professor in the Department of Biomedical Data Science at Stanford University School of Medicine and is a member of the Board of Directors of the International Society of Computational Biology, serving from 2022 to 2025.
Francisco teaches BIODS-235: "Best practices for developing data science software for clinical and healthcare applications" every Winter quarter. -
Li Gong
Scientific Data Curator 3, Biomedical Data Science
Current Role at StanfordI am a senior scientific curator at PharmGKB, and also serves as the program manager for the Stanford ClinGen team and coordinator for the ClinGen Pharmacogenomics Working Group.
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Matthew Lungren
Adjunct Professor, Biomedical Data Science
BioDr. Lungren is Chief Data Science Officer for Microsoft Health & Life Sciences where he focuses on translating cutting edge technology, including generative AI and cloud services, into innovative healthcare applications. As a physician and clinical machine learning researcher, he maintains a part-time clinical practice at UCSF while also continuing his research and teaching roles as adjunct professor at Stanford University.
Prior to joining Microsoft, Dr Lungren was a clinical interventional radiologist and research faculty at Stanford University Medical School where he led the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI). He later served as Principal for Clinical AI/ML at Amazon Web Services in World Wide Public Sector Healthcare, focusing on business development for clinical machine learning technologies in the public cloud.
His scientific work has led to more than 150 publications, including work on multi-modal data fusion models for healthcare applications, new computer vision and natural language processing approaches for healthcare specific domains, opportunistic screening with machine learning for public health applications, open medical data as public good, prospective clinical trials for clinical AI translation, and application of generative AI in healthcare. He has served as advisor for early stage startups and large fortune-500 companies on healthcare AI technology development and go-to-market strategy. Dr. Lungren's work has been featured in national news outlets such as NPR, Vice News, Scientific American, and he regularly speaks at national and international scientific meetings on the topic of AI in healthcare.
Dr. Lungren is also a top rated instructor on Coursera where his AI in Healthcare course designed especially for learners with non-technical backgrounds has been completed by more than 20k students around the world - enrollment is open now: https://www.coursera.org/learn/fundamental-machine-learning-healthcare
