Virtual Seminars
Our Virtual Seminar Series is a monthly event spotlighting the latest innovations in computational and digital health. Each session features engaging talks from world-class researchers—including both Duke-affiliated experts and invited speakers from across academia, industry, and healthcare.
Covering topics such as artificial intelligence (AI), high-performance computing (HPC), extended reality (XR), and wearable technologies, the series offers a front-row seat to emerging discoveries shaping the future of healthcare.
Talks are hosted live in a fully virtual format, making them accessible to participants anywhere in the world. Each session is also recorded and shared on the Center’s YouTube channel, allowing you to revisit key insights or catch up on missed events.
Whether you’re a researcher, clinician, student, or simply curious about the technologies transforming medicine, the Virtual Seminar Series provides:
- Accessible research presentations on cutting-edge topics
- Opportunities for discussion and networking with thought leaders
- A growing archive of talks for on-demand learning
Join us each month as we connect ideas, inspire collaborations, and advance the conversation in computational and digital health.
Events
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Virtual Seminar with Philipp Gutruf: “Wearable and Implantable Systems for Seamless High-Fidelity Diagnostics and Therapeutics”
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.
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Virtual Seminar with Ricardo Henao
Topic to be announced
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Virtual Seminar with David A. Bader: “High-Performance Graph Analytics for Motif Finding in Neuroscience Connectome Graphs and Beyond Using Arachne”
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.