Digital Twin

Digital twins are virtual representations of physical systems, aiming to mirror their behavior and enable predictive modeling, optimization, and analysis. Current research emphasizes developing digital twins across diverse domains, from supercomputers and transportation systems to healthcare and manufacturing, often employing machine learning models (like transformers and neural ODEs), graph-based methods, and large language models for data integration, prediction, and control. This technology's significance lies in its ability to improve efficiency, safety, and decision-making in various sectors by providing a virtual testing ground for complex systems and facilitating data-driven insights.