This workshop is designed for engineering students to understand how AI/ML tools can be used to improve simulation and modeling accuracy.

Participants will learn to:

• Design and analyze experiments using modern techniques such as Latin Hypercube Sampling, sliced designs, adaptive design, and Bayesian sampling
• Build fast and accurate surrogate models for complex simulations using Gaussian processes and other machine learning methods
• Perform uncertainty propagation, sensitivity analysis, and statistical calibration – key skills required in the industry for robust engineering decision-making