Stanford University
Showing 11-20 of 42 Results
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Li Gong
Scientific Data Curator 3, Biomedical Data Science
Current Role at StanfordProgram manager and senior scientific curator for ClinPGx, coordinator for the ClinGen Pharmacogenomics Interpretation Committee (PGxIC).
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Jason Hilton
Senior Research Engineer, Biomedical Data Science
Current Role at StanfordPI & Director, Lattice
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Dr Mohit Kaushal MD
Adjunct Professor, Biomedical Data Science
BioDr. Mohit Kaushal is an accomplished entrepreneur, investor, and physician with a distinguished career spanning clinical medicine, academia, public policy and industry. He has served as an investor and board member for numerous public and private transformative companies, including Oak Street Health (NYSE: OSH, acquired by CVS Health, NYSE: CVS), Humedica (acquired by Optum, NYSE: UNH), RxAnte (acquired by Millennium), Change Healthcare (acquired by Emdeon), Universal American (NYSE: UAM, acquired by WellCare, NYSE: WCG), goBalto (acquired by Oracle, NYSE: ORCL), CitiusTech (acquired by Baring), Wellframe (acquired by HealthEdge), and George Clinical (acquired by Hillhouse).
During the Obama administration, Dr. Kaushal served on the White House Health IT Task Force, contributing to the implementation of the Affordable Care Act’s technology initiatives and testifying before Congress on the role of technology and payment reform in Medicare. He also established and led the first dedicated healthcare team at the Federal Communications Commission, where his work included partnering with the FDA to streamline regulation of converged telecommunications, analytics, and medical devices, ultimately resulting in the FDA’s mobile medical applications guidance. His team also restructured the Rural Healthcare Fund into the Healthcare Connect Fund, aligning its resources with broader healthcare technology and payment reforms.
In academia, Dr. Kaushal is an Adjunct Professor in the Department of Biomedical Data Science at Stanford University, which integrates AI, biomedical informatics, biostatistics and computer science to advance precision health. His teaching emphasizes the application of data—ranging from molecular and tissue-level information to imaging, EHR, biosensors, and population health—to improve medical outcomes.
He remains active in public policy as a Scholar in Residence at the Duke-Margolis Center for Health Policy and was previously a Visiting Scholar at the Brookings Institution. His policy work includes previous appointments to the FDASIA Workgroup of the Health IT Policy Committee and the National Committee on Vital and Health Statistics, advising HHS on data access and use.
Dr. Kaushal is an emergency physician by training, holds an MBA from Stanford University, and earned his MD with distinction from Imperial College London. -
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
