The emerging field of digital twins, virtual replicas of physical systems, represents a significant frontier for machine learning research with broad applications across industries. This social will bring together researchers interested in the unique challenges of leveraging ML to create, improve, and deploy digital twins.

This will be an interactive discussion focusing on key questions broadly related to the fidelity, scientific accuracy and limitations of ML for digital twins.

The session will feature brief introductions from participants working in this area, followed by open discussion and potential collaboration opportunities. We welcome researchers from diverse ML backgrounds including reinforcement learning, generative modeling, time-series forecasting, and domain experts from industries leveraging digital twins.

Join us to explore this rapidly evolving intersection of ML theory and practical applications transforming industries including manufacturing, healthcare, and climate science.