Skip to main content
King Abdullah University of Science and Technology
Applied Mathematics and Computational Science
AMCS
Applied Mathematics and Computational Science
  • Study
    • Prospective Students
    • Current Students
  • Research
    • Research Areas
    • Research Groups
  • People
    • All People
    • Faculty
    • Affiliate Faculty
    • Instructional Faculty
    • Research Scientists
    • Research Staff
    • Postdoctoral Fellows
    • Administrative Staff
    • Alumni
    • Students
  • News
  • Events
  • SIAM Student Chapter
  • CEMSE Division
  • About
  • Apply

PCA

Reduced-Order High Fidelity Simulations of Reacting Flows Using Low Dimensional Manifolds and Machine Learning

Hong G. Im, Professor, Mechanical Engineering; Deputy Chair, Clean Energy Research Platform, King Abdullah University of Science and Technology (KAUST)

Apr 7, 14:30 - 15:30

B1 R3119

machine learning Applied Machine Learning principal component analysis PCA computational singular perturbation renewable energy flow problems computational simulations

This talk will provide an overview of historical developments in mathematical and computational approaches to reduced order models for accelerated high fidelity reacting flow simulations in modern computing hardware.

Applied Mathematics and Computational Science (AMCS)

Footer

  • A-Z Directory
    • All Content
    • Browse Related Sites
  • Site Management
    • Log in

© 2025 King Abdullah University of Science and Technology. All rights reserved. Privacy Notice