Expected outcomes & broader impact

This initiative will establish a foundational framework for Physics-AI Digital Twins, unifying first-principles modeling, scientific machine learning, real-time sensing, and uncertainty quantification across diverse engineering and biomedical domains.

Core technical & community deliverables

• Advanced computational frameworks: Multi-scale and multiphysics modeling tools that dramatically reduce computational costs and bridge the sim-to-real gap
• Open community resources: Transferable software tools, open datasets, and benchmark problems spanning cardiovascular care, neuroengineering, additive manufacturing, metamaterials, and autonomous systems
• Grounded & trustworthy AI: Embedded physics-informed constraints, uncertainty quantification (UQ), and rigorous verification and validation (V&V) procedures to ensure predictions remain interpretable, safe, and reliable

Translation & societal value

• Interdisciplinary adoption: Practical pathways for technology transfer across healthcare networks, manufacturing institutes, robotics centers, national laboratories, and industry partners
• High-impact applications: Scalable solutions addressing critical societal challenges in personalized healthcare, supply chain resiliency, sustainability, and national security

Strategic vision & growth

• Pioneering leadership: Positioning CMU as a national leader and interdisciplinary hub at the intersection of AI, physics, and digital engineering
• Center-scaled expansion: Laying the foundational research and collaborative ecosystem required to support future major center-scale proposals across federal research agencies, health institutes, defense programs, and enterprise technology partners