Reduced order models can be powerful tools to predict, understand and control. I will demonstrate how modern tools (Deep Koopman operators) can be used to better understand and predict spatio-temporal chaotic systems.

Pierre Gentine

Pierre Gentine

Dr. Pierre Gentine is a Professor in the Department of Earth and Environmental Engineering and the Department of Earth and Environmental Sciences at Columbia University. He directs the NSF Science and Technology Center ‘Learning the Earth with Artificial Intelligence and Physics’ and the Graduate Program in Earth and Environmental Engineering. His research focuses on the multiscale nature of the hydrologic and carbon cycle using remote sensing, in situ observations, models, and machine learning. Dr. Gentine earned his PhD in Civil and Environmental Engineering from MIT in 2010 and joined Columbia as a faculty member the same year.

SUMMARY OF ACTIVITIES/INTERESTS

  • AI on Graphs
  • Emerging Behavior
  • Reduced Order Systems