Dr. Schmiedmayer is the Assistant Director Digital Health and postdoctoral researcher at the Byers Center for Biodesign at Stanford University, focusing on the applications of computer science innovations in medicine. He focuses on digital health solutions, including AI-driven systems and healthcare interoperability. He is leading the development of the Stanford Spezi framework and ecosystem.

He earned his doctoral degree at the Technical University of Munich, where he studied software engineering, mobile-based systems including smart devices, the applications and integration of machine learning techniques, and the evolution of web service-based distributed systems. He holds a master's and bachelor's degree in computer science from the Technical University of Munich.

Current Research and Scholarly Interests

Paul Schmiedmayer's research applies computer science research to medicine, enabling digital health innovations. These include machine learning applications and deployments, heterogeneous connected devices, health data standards such as FHIR, and software engineering best practices.
He leads the development of the Stanford Spezi framework and ecosystem, enabling the rapid development of digital health innovations. He is a co-instructor of the Building for Digital Health (CS342) course.

Lab Affiliations

All Publications

  • CardinalKit: open-source standards-based, interoperable mobile development platform to help translate the promise of digital health. JAMIA open Aalami, O., Hittle, M., Ravi, V., Griffin, A., Schmiedmayer, P., Shenoy, V., Gutierrez, S., Venook, R. 2023; 6 (3): ooad044


    Smartphone devices capable of monitoring users' health, physiology, activity, and environment revolutionize care delivery, medical research, and remote patient monitoring. Such devices, laden with clinical-grade sensors and cloud connectivity, allow clinicians, researchers, and patients to monitor health longitudinally, passively, and persistently, shifting the paradigm of care and research from low-resolution, intermittent, and discrete to one of persistent, continuous, and high resolution. The collection, transmission, and storage of sensitive health data using mobile devices presents unique challenges that serve as significant barriers to entry for care providers and researchers alike. Compliance with standards like HIPAA and GDPR requires unique skills and practices. These requirements make off-the-shelf technologies insufficient for use in the digital health space. As a result, budget, timeline, talent, and resource constraints are the largest barriers to new digital technologies. The CardinalKit platform is an open-source project addressing these challenges by focusing on reducing these barriers and accelerating the innovation, adoption, and use of digital health technologies. CardinalKit provides a mobile template application and web dashboard to enable an interoperable foundation for developing digital health applications. We demonstrate the applicability of CardinalKit to a wide variety of digital health applications across 18 innovative digital health prototypes.

    View details for DOI 10.1093/jamiaopen/ooad044

    View details for PubMedID 37485467

    View details for PubMedCentralID PMC10356573

  • Reducing the Impact of Breaking Changes to Web Service Clients During Web API Evolution Schmiedmayer, P., Bauer, A., Bruegge, B., IEEE IEEE COMPUTER SOC. 2023: 1-11
  • Global Software Engineering in a Global Classroom Schmiedmayer, P., Chatley, R., Bernius, J., Krusche, S., Chaika, K., Krinkin, K., Bruegge, B., IEEE Comp Soc IEEE COMPUTER SOC. 2022: 113-121