Menger Day Lecture by George Karniadakis: "From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus?"
Speaker: George Karniadakis, Charles Pitts Robinson and John Palmer Barstow Professor of Applied Mathematics at Brown University
Title: "From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus?"
Abstract: We will review physics-informed neural networks (PINNs) and summarize available extensions for applications in computational science and engineering. We will also introduce new neural networks that learn functionals and nonlinear operators from functions and corresponding responses for
system identification. Finally, we will present first results on the next generation of these architectures to
biologically plausible designs based on spiking neural networks that are more efficient and closer to
human intelligence. We will present applications of physics-informed machine learning in engineering,
physics, and biomedicine.
RSVP