Events
Engage With Our Community
At the Duke Center for Computational and Digital Health Innovation, we believe that innovation thrives in an open and collaborative environment.
We are excited to offer a range of events that provide opportunities for the Duke community and beyond to connect, share ideas, and spark new collaborations.
Whether you are a researcher, clinician, student, or industry partner, our events are designed to engage and inspire.
Virtual Seminar Series
Our Virtual Seminar Series brings together thought leaders and experts in computational and digital health. These seminars are open to both Duke affiliates and the public, offering perceptive insights into the latest research and innovations.
Espresso Chats
Espresso Chats are informal, 30-minute virtual conversations designed to connect students directly with alumni, industry professionals, and thought leaders in digital health.
Events
-
-
Community of Practice: Duke REVS – Digital Health Info Session
Location: Wilkinson 017 534 Research Dr.
-
-
Center for Computational and Digital Health Innovation Demo Day
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.
-
-
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.
-
-
Virtual Seminar with Ricardo Henao
Topic to be announced
-
-
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.