On June 24, 2025, the Sorbonne Center for Artificial Intelligence (SCAI) hosted a full-day event dedicated to Digital Twins — exploring their theoretical foundations, industrial applications, and future research directions.

Held oat SCAI, the event brought together leading academic and industry experts with an audience primarily composed of PhD students in artificial intelligence and machine learning (Sound.ai). Many attendees came from outside the speakers’ core disciplines, which made the interdisciplinary nature of the day all the more enriching.

Morning – Foundations and Broader Perspectives

Following welcoming remarks and representatives from the MSCA program, the morning featured three insightful talks:

• Anastase Charantonis (Inria Paris) introduced the concept of digital twins in the context of weather and climate forecasting, a domain where physics-based simulation meets data-driven insights.
• Alejandro Ribes (EDF – SINCLAIR Project) shared lessons from developing physics-informed deep learning for industrial digital twins, emphasizing the synergy between AI models and domain knowledge.
• Abel Dembele (SUEZ) presented real-world applications of digital twins in environmental infrastructure, focusing on monitoring, forecasting, and optimization for sustainable systems.

Afternoon – Real-World Cases and Research Prototypes

The afternoon shifted toward cutting-edge research and applied use cases:

• Ulisse Ferrari (Institut de la Vision) introduced a digital twin of the human eye, combining computational neuroscience, perceptual modeling, and strategies for vision restoration.
• Anne-Virginie Salsac (CNRS, UTC – Université de Technologie de Compiègne) joined remotely to discuss the challenges of applying digital twins in healthcare, particularly in modeling biological systems and surgical environments.

A Day of Cross-Disciplinary Exchange
Beyond the presentations, the event sparked stimulating discussions across disciplines. It highlighted how digital twins are becoming a key convergence point between simulation, data, AI, and engineering — with applications spanning industry, environment, and human health.