The Duke Summit on AI for Health Innovation is open to healthcare professionals, industry leaders, and business professionals, including faculty, students, and staff from Duke and other academic institutions. The...
Espresso Chats are informal, 30-minute virtual conversations designed to connect students directly with alumni, industry professionals, and thought leaders in digital health. There’s no formal presentation—just candid conversation about careers, innovation, and lessons learned....
Location to be announced. About Communities of Practice Communities of Practice (CoPs) are at the heart of the Computational and Digital Health Innovation Certificate. Open to trainees, clinicians, and faculty,...
Speaker: Dr. Michael Rubinstein, November 6 @ 3:00 PM – 4:00 PM
Location to be announced. About Communities of Practice Communities of Practice (CoPs) are at the heart of the Computational and Digital Health Innovation Certificate. Open to trainees, clinicians, and faculty,...
Espresso Chats are informal, 30-minute virtual conversations designed to connect students directly with alumni, industry professionals, and thought leaders in digital health. There’s no formal presentation—just candid conversation about careers, innovation, and lessons learned....
Speaker: Dr. Yang You, Virtual Event: December 4 @ 9:00 AM – 10:00 AM
Duke AI Health, in partnership with Duke Health and the Pratt School of Engineering, will be hosting the Health Data Science Poster Showcase on Friday, December 12, from 11:30 AM...
Location: Bseisu Cafe About Communities of Practice Communities of Practice (CoPs) are at the heart of the Computational and Digital Health Innovation Certificate. Open to trainees, clinicians, and faculty, CoPs...
Speaker: Monica Agrawal
About 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. There’s no formal presentation—just candid conversation about careers, innovation,...
What if a machine could watch a video and write down the equations of motion? I’ll discuss our recent work toward this goal — systems that learn to discover the hidden state variables and governing dynamics directly from raw visual data. These discovered Neural State Variables and Neural State Vector Fields not only reproduce trajectories but also reveal the structure of these dynamical systems: equilibrium, stability, and chaos. The results suggest a path toward a self-driven AI scientist.