Speaker
Description
The integration of Digital Twin technology with AI Engine is transforming how research and industry understand, predict, and optimize complex systems. Building upon collaborative initiatives between CERN, InnoSuisse, and industrial partners, this talk explores how open-science can be extended into scalable, data-intelligent frameworks for real-world applications.
At the core lies the AI-enabled computational architecture that connects simulation, experimentation, and decision intelligence. By coupling CERN’s high-fidelity modeling environment with industrial process data, this framework enables predictive control, dynamic optimization, and explainable risk management across domains such as supply chain, healthcare and finance.
The presentation will illustrate case studies where AI-powered digital twins accelerate innovation, improve operational resilience, and bridge the gap between scientific modeling and industrial deployment. It will also outline the vision for an applied mathematics alliance, fostering reproducible, transparent, and AI-augmented collaboration between academia and industry.