Fahime Seyedheydari

Physics‐Guided Monte Carlo Surrogate Modeling for Optical Properties Inference and Spectral Prediction From Limited Experimental Data

ABSTRACT We present a physics‐guided neural framework that combines Monte Carlo simulations with experimental measurements to characterize optical properties and predict spectral responses at unseen conditions. The hybrid model jointly learns from simulations with complete optica...

Deep learning-based surrogate model for generation of wood microstructures

A machine learning-based surrogate model for efficient wood microstructure generation compatible with a physics-based model is developed. The model is based on the U-Net neural network, a variant of convolutional neural network which, due to its architecture, is suitable for imag...