This talk explores how AI-driven techniques — including machine learning — can enhance time-series prediction, attractor reconstruction, and digital twin development. Topics include supervised and unsupervised prediction of critical transitions in complex systems such as climate and power grids, and data-driven model discovery using Kolmogorov-Arnold Networks.
Case studies cover AI-assisted forecasting of the Atlantic Meridional Overturning Circulation, and a vision for an ongoing project on physical AI addressing fundamental challenges in electrical and computer engineering across multiple disciplines.
Speaker(s): Walt Slade,
Agenda:
Doors Open 6:00pm
Networking from 6:00-6:30pm
Announcements and Welcome-6:30- 6:45 pm, Jim Cale
Did Y'know-6:45-7:00 pm- Scott Evans
Technical Presentation 7:00-8:00 pm, Dr. Panahi
A light snack will be available, probably Pizza and Soft drinks
Room: B101, Bldg: Engineering, 400 Isotope Dr., Fort Collins, Colorado, United States, 80525