Eshit Dhiman

From Newton to Neural Networks: A Review of Data-Driven Physical Modelling and the Rise of Physics-Informed AI

This review examines the evolution of physical modelling from classical first-principles approaches to contemporary data-driven and physics-informed learning frameworks, with a central focus on Physics-Informed Neural Networks and related hybrid methods that integrate governing laws into learning algorithms to improve prediction, generalization, and physical plausibility.