[NALA - Virtual] Physical AI: Building High-Fidelity Digital Twins with Matterix

How do we move beyond standard simulation to create high-fidelity digital twins that truly mirror the real world?

Simulation is critical for modern robotics, but the "sim-to-real" gap remains a significant bottleneck, especially in complex environments involving fluids, deformable objects, and chemical processes.

Join the Canadian Physical AI Institute (CPAI) for an exclusive session with Kourosh Darvish, Staff Scientist at the University of Toronto, as we explore Matterix—a new multi-scale, GPU-accelerated simulation framework designed to create high-fidelity digital twins.

While originally developed for chemistry laboratory automation and self-driving labs, the concepts covered are broadly applicable to robotics domains requiring complex manipulation and perception.

🚀 What You Will Learn
This session is designed to provide both a "behind-the-scenes" look at real research projects and a practical walkthrough of key concepts.

• Introduction to Matterix: Discover a framework built on NVIDIA Isaac Sim and Isaac Lab that integrates realistic physics and photorealistic rendering with a modular, GPU-accelerated semantics engine.
• Multi-Scale Modeling: Learn how to simulate beyond simple rigid bodies, including powder and liquid dynamics, device functionalities, heat transfer, and chemical reaction kinetics.
• Hybrid Intelligence: Explore how to model both logical states and continuous behaviors to represent workflows across multiple levels of abstraction.
• Digital Twin Value: Gain a clear view of where digital twins add value, specifically in policy training, workflow development, system co-design, and safety analysis
• Real-World Tradeoffs: An honest discussion on when simulation works well, when it breaks down, and how to navigate those tradeoffs in real projects.

More Information: https://luma.com/tp20xcls