The most interesting part of my project is how it merges artificial intelligence with localized deformation analysis in materials science. Traditional Digital Image Correlation (DIC) techniques are powerful but often limited in terms of resolution, speed, and adaptability. By incorporating AI/ML approaches, we can enhance precision, automate pattern recognition, and potentially uncover deformation behaviors that were previously difficult to detect.
This fusion of machine learning and material science is exciting because it opens up new possibilities for real-time analysis, predictive modeling, and even applications beyond materials—such as structural health monitoring and biomechanics. It’s fascinating to explore how AI can push the boundaries of what we currently understand about material behavior under stress.
