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Center for Computational and Digital Health Innovation
5 events found.

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  • August 2026

  • Mon 24
    Photo Of People Leaning On Wooden Table

    Community of Practice: Duke REVS – Digital Health Info Session

    August 24 @ 4:00 pm - 5:00 pm

    Location: Wilkinson 017 534 Research Dr.

  • September 2026

  • Fri 25
    Wilkinson Building

    Center for Computational and Digital Health Innovation Demo Day

    September 25

    The Center for Computational and Digital Health Innovation will host a Center for Computational and Digital Health Innovation Demo Day, bringing together faculty, students, researchers, and members of the broader Duke and local community to experience interactive demonstrations of computational and digital health research.

  • October 2026

  • Wed 7
    Philipp Gutruf

    Virtual Seminar with Philipp Gutruf: “Wearable and Implantable Systems for Seamless High-Fidelity Diagnostics and Therapeutics”

    October 7 @ 2:00 pm - 3:00 pm

    Advances in materials and fabrication concepts for soft electronics coupled with miniaturization of wireless energy transfer enables the creation of high-performance electronic and optoelectronic systems with footprint and physical properties matched to biology. This talk explores the creation of such systems and discusses applications in the context of imperceptible body-worn devices for the assessment of physiology.

  • November 2026

  • Wed 11
    Ricardo Henao

    Virtual Seminar with Ricardo Henao

    November 11 @ 2:00 pm - 3:00 pm

    Topic to be announced

  • December 2026

  • Wed 2
    David Bader

    Virtual Seminar with David A. Bader: “High-Performance Graph Analytics for Motif Finding in Neuroscience Connectome Graphs and Beyond Using Arachne”

    December 2 @ 2:00 pm - 3:00 pm

    The growth of network-structured data across domains like neuroscience and cybersecurity demands scalable graph analytics, but complex tasks like subgraph isomorphism remain accessible only to high-performance computing (HPC) specialists. Arachne is an open-source framework that democratizes high-performance graph analytics through a Python interface while abstracting parallelism complexities.

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  • Research
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    • Digital Twin Initiative
    • REVS – Digital Health
  • Certificate Program
    • Certificate Curriculum
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