School of Medicine


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  • Paul Schmiedmayer

    Paul Schmiedmayer

    Instructor, Computational Medicine
    Research Engineer, School of Medicine - MDRP'S - Biodesign Program

    Current Research and Scholarly InterestsDr. Schmiedmayer's research investigates scalable, intelligent, data-driven systems that leverage patient data and connected devices to provide real-time, personalized healthcare. He aims to validate these solutions by deploying AI-based models on resource-constrained, patient-facing devices, such as smartphones and smart devices, ensuring that personalized medicine is both cost-effective and privacy-preserving.

  • Nigam H. Shah, MBBS, PhD

    Nigam H. Shah, MBBS, PhD

    Professor of Medicine (Computational Medicine), of Biomedical Data Science and, by courtesy, of Computer Science

    Current Research and Scholarly InterestsWe answer clinical questions using aggregate patient data at the bedside. The Informatics Consult Service (https://greenbutton.stanford.edu/) put this idea in action and led to the creation of Atropos Health. We build predictive models that allow taking mitigating actions, keeping the human in the loop.

  • Walter Sujansky

    Walter Sujansky

    Adjunct Professor, Division of Computational Medicine

    BioWalter Sujansky, MD PhD is an Adjunct Professor of Biomedical Informatics at the Stanford Center for Biomedical Informatics Research in the Stanford Department of Medicine. Dr. Sujansky co-teaches BMI-210 Modeling Biomedical Systems, where he lectures on a variety of topics, including deep neural networks, probabilistic reasoning, electronic health records, and health data integration and interoperability. He also advises students in the Biomedical Data Science Graduate Program, an interdisciplinary graduate and postdoctoral training program that is part of the Department of Biomedical Data Science. His research interests include the modeling of biomedical concepts based on formal logic and the engineering of features for biomedical machine learning algorithms.

    Dr. Sujansky earned an M.D. and a Ph.D. in Medical Informatics from Stanford University, where his doctoral research addressed heterogeneous database integration and clinical decision support. He also earned a B.A. in Economics from Harvard University.

    Dr. Sujansky is also the managing consultant at Sujansky & Associates, LLC, a consulting firm that specializes in the representation, management, and analysis of clinical data in information systems. In this capacity, his work focuses on the modeling of complex biomedical data related to patient phenotyping, clinical genomics, quality measurement, automated decision support, and machine learning. His firm has helped to develop shared computing resources such as the California Joint Replacement Registry and the Laboratory Interoperability Data Repository. The firm's clients include the federal and state governments, non-profit organizations, health information system developers, and drug/device manufacturers. Dr. Sujansky also provides forensic analysis of health information technologies for medical malpractice and intellectual property litigation.