# Parametric Shape Optimization with Differentiable FEM **URL:** \ **Category:** Showcase\ **Tags:** optimization, tesseract-jax\ **Created:** [July 11, 2025, 9:55am UTC](https://si-tesseract.discourse.group/t/parametric-shape-optimization-with-differentiable-fem/98 "2025-07-11T09:55:26Z")\ **Posts on this page:** 1\ **Page:** 1
**Author:** ![Alessandro](https://yyz1.discourse-cdn.com/flex009/user_avatar/si-tesseract.discourse.group/alessandro/32/37_2.png) [@Alessandro](https://si-tesseract.discourse.group/u/Alessandro)\ **Post date:** [July 11, 2025, 9:55am UTC](https://si-tesseract.discourse.group/t/parametric-shape-optimization-with-differentiable-fem/98/1 "2025-07-11T09:55:26Z")
Shape optimization is a natural application of many of the ideas which went into building the Tesseract framework. We wrote a demo where we solve an optimization problem to find structural configurations that minimize compliance using gradient-based optimization through JAX-FEM and geometry processing. The pipeline involves two Tesseracts with computation orchestrated via Tesseract-JAX; it’s interesting to note how this makes composing Tesseracts look exactly like composing local Python functions, and also how libraries like `optax` can be used in conjunction with Check out the demo [here](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/demo/fem-shape-optimization.html) ![f98ad6439186049c88905240f15c894d89455c92203cfe832418e4ffcc5c034a](https://canada1.discourse-cdn.com/flex009/uploads/si_tesseract/original/1X/bd58b8286212916b32b3f04309ff9a40274654db.png) > **[Parametric Shape Optimization with Differentiable FEM Simulation](https://docs.pasteurlabs.ai/projects/tesseract-core/latest/content/demo/fem-shape-optimization.html)** > > In this tutorial, you will learn how to: Build a Tesseract that wraps a differentiable finite-element solver from jax-fem., Build a Tesseract that uses finite differences under the hood to enable d...