Physophia Lab

Physical Engineering Intelligence

More than a world model: an end-to-end system, from physical understanding to real-world engineering.

Physics · Intelligence · Wisdom
Adaptive latent physics · live

Our world models learn how fluids move, how structures deform, how a printed part warps. Engineers use them to design wings and hulls, and to correct a part before it is printed again. Every measured part teaches the model. Others model the world. We plug ours into the workshop.

UnderstandEngineerBuildMeasureLearn
Technology

From understanding to engineering,
end to end.

I

Spatial Reasoning

Geometry, terrain, imagery and sensor data fused into one latent picture of the physical scene.

II

Physical Understanding

How fluids, structures and heat evolve and respond to action: forward from causes, backward from consequences.

III

Engineering Practice

Wings, hulls and printed parts designed in latent space and corrected from what the factory measures.

Validated on Aircraft wing generationShip hull resistanceThermal distortion compensationImpact forensicsMulti-Re turbulenceWildfire risk
Applications

Reshaping engineering and manufacturing with physical intelligence.

From latent space to the finished part, one block at a time.

Why Physophia

Others model the world. We plug it into the workshop.

Spatial world models generate scenes. Surrogates speed up one task. We combine engineering-grade physics with learned dynamics, and hand engineers something they can build.

Engineering-grade physics

Continuum, fluid, thermal, structural.

Learned dynamics

Long-horizon, multi-regime rollout.

Bidirectional reasoning

Forward generation, inverse inference.

Closed loop to fabrication

Geometry, process and control you can ship.

Platform

One stack. Three layers.

Model

PHYSOPHIA World

Foundation models for physical dynamics. API, private licensing, vertical adaptation.

Simulation

PHYSOPHIA Sim

Generative, interactive simulation infrastructure. Cloud, VPC or on-prem.

Agent

PHYSOPHIA Agent

Autonomous engineering agents that propose, evaluate and refine designs inside your workflow.

Team

Berkeley mechanics depth. Frontier AI execution.

Prof. Shaofan Li

Scientific anchor · Professor of Applied & Computational Mechanics, UC Berkeley

Thirty years in computational mechanics, multiscale modeling, inverse problems and AI-aided engineering design, joined by a team spanning world-model AI, DNS/CFD, FEM and multiphysics.

30+YEARS
23,100+CITATIONS
66H-INDEX
Work with us

Land in engineering. Expand into Physical AI.

We start where simulation is expensive and design cycles are slow. Bring us a benchmark.