Learn about the powerful combination of physical modeling and machine learning in this webinar led by Dr. Chris Rackauckas, Lead Developer of SciML Open Source Software Organization and VP of Modeling and Simulation at JuliaHub. Explore how combining structured scientific differential equation models with unstructured data-driven machine learning models can enhance simulator performance and accuracy while maintaining the robustness and explainability of mechanistic dynamical models. Discover the practical applications of SciML in industrial engineering, understand its unique advantages for modeling complex systems, and examine how it differs from traditional machine learning approaches. Gain insights into accelerating simulators and improving system approximations through this innovative computational approach that bridges scientific computing with machine learning methodologies.