Introduction to Machine Learning for Science 2026

This introductory webinar series explores the transformative role of neural networks (NNs) in science and engineering, with a focus on their growing potential to revolutionize data analysis and computational modeling. As a powerful branch of artificial intelligence, neural networks serve as surrogate models capable of efficiently approximating complex systems with high accuracy. This webinar will provide an overview of the fundamental principles of neural networks, emphasizing their versatility across engineering applications—including predicting the behavior of composite materials, optimizing design processes, and supporting biomedical analysis.