This cross-cutting research theme focuses on the integration of computational modeling, simulation, and data-driven methods to address complex scientific and engineering challenges across diverse fields. It leverages advanced algorithms, high-performance computing, and mathematical frameworks to enable predictive modeling, design optimization, and decision-making in systems that are too intricate for purely experimental approaches. Research under development includes multi-scale simulation methods, uncertainty quantification, big data analytics, artificial intelligence, high-fidelity simulations, machine learning, model order reduction, simulation-based design optimization, and quantum computing for applications in climate science, aerospace, biological systems, advanced materials, and energy systems.