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Julian Panetta

Assistant Professor

UC Davis

Biography

Julian Panetta is an Assistant Professor of Computer Science at University of California, Davis. His research interests lie primarily in the domain of physical simulation, geometry processing, and optimization-based inverse design for digital fabrication. He develops efficient computational techniques for designing physical objects that meet specific performance goals and can be directly brought into the real world using additive fabrication or CNC machines. He is especially motivated to invent algorithms empowering users to exploit these technologies’ currently untapped potentials for a broad range of applications, from professional, industrial settings to casual use.

Interests

  • Digital Fabrication
  • Physical Simulation
  • Inverse Problems

Education

  • PhD in Computer Science, 2017

    New York University

  • BS in Computer Science, 2010

    California Institute of Technology

Positions

  • Assistant Professor, 2020-

    University of California, Davis

  • Postdoc, 2017-2020

    École Polytechnique Fédérale de Lausanne

Publications

Computational Homogenization for Inverse Design of Surface-based Inflatables

We develop an effcient homogenization technique for analyzing the contractions and stiffnesses of periodic inflatable patterns and use it for inverse design of general surface-based inflatables.
Yingying Ren, Julian Panetta, Seiichi Suzuki, Uday Kusupati, Florin Isvoranu, Mark Pauly
ACM SIGGRAPH 2024
PDF Supplement

A Neural-Preconditioned Poisson Solver for Mixed Dirichlet and Neumann Boundary Conditions

We introduce a neural-preconditioned iterative solver for Poisson equations with mixed boundary conditions.
Weixian (Kai) Lan, Elias Gueidon, Ayano Kaneda, Julian Panetta, Joseph Teran
ICML 2024
PDF Code Video

Computational Design of Flexible Planar Microstructures

We design flexible microstructures that emulate desired elastic materials over finite regions of macrosopic strain space.
ACM SIGGRAPH Asia 2023
PDF Supplement

C-shells: Deployable Gridshells with Curved Beams

We introduce a computational pipeline for simulating and designing C-shells, deployable structures composed of beams with curved planar rest shapes.
Quentin Becker, Seiichi Suzuki, Yingying Ren, Davide Pellis, Julian Panetta, Mark Pauly
ACM SIGGRAPH Asia 2023
PDF Supplement

Computational Exploration of Multistable Elastic Knots

We present an algorithmic approach to discover, study, and design multistable elastic knots, physical realizations of closed curves embedded in 3-space.
ACM SIGGRAPH 2023
PDF Code

Shape from Release: Inverse Design and Fabrication of Controlled Release Structures

Objects with different shapes can dissolve in significantly different ways inside a solution. Predicting different shapes’ dissolution dynamics is an important problem especially in …
Julian Panetta, Haleh Mohammadian, Emiliano Luci, Vahid Babaei
ACM SIGGRAPH Asia 2022
PDF Fast Forward Presentation 5min Presentation Full Presentation

Efficient Layer-by-Layer Simulation for Topology Optimization

Topology optimization and additive manufacturing together enable the optimal design and direct fabrication of complex geometric parts with groundbreaking performance for diverse applications. However …
Weixian (Kai) Lan, Julian Panetta
SCF 2022
PDF Code

Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment

We present a computational inverse design framework for a new class of volumetric deployable structures that have compact rest states and deploy into bending-active 3D target surfaces. Umbrella meshes …
ACM SIGGRAPH 2022   –   *Joint First Authors
PDF Supplement

Topology Optimization via Frequency Tuning of Neural Design Representations

By tuning the scale hyperparameter of a neural design representation based on a Fourier feature network, we can control the smoothness of designs without explicit smoothing filters.
Nikan Doosti, Julian Panetta, Vahid Babaei
SCF 2021
PDF

Computational Inverse Design of Surface-based Inflatables

Fusing two sheets along parallel curves creates pockets that inflate into tubes and deform into a curved 3D shape; we optimize the fusing curve network to reproduce an input geometry.
ACM SIGGRAPH 2021
PDF Supplement Code Fast Forward Presentation 5min Presentation Full Presentation

Weaving with Curved Ribbons

We optimize the shapes of curved planar laser-cut ribbons that weave into faithful approximations of smooth free-form geometries.
Yingying Ren, Julian Panetta, Tian Chen, Samuel Poincloux, Christopher Brandt, Alison Martin, Mark Pauly
ACM SIGGRAPH 2021
PDF Supplement Video 5min Presentation Full Presentation

Bistable Auxetic Surface Structures

We optimize patterns that, when cut into a flat rubber sheet, produce bistable auxetic metamaterials encoding curved target geometries.
Tian Chen, Julian Panetta, Max Schnaubelt, Mark Pauly
ACM SIGGRAPH 2021
PDF 5min Presentation Full Presentation

A Low-Parametric Rhombic Microstructure Family for Irregular Lattices

New fabrication technologies have significantly decreased the cost of fabrication of shapes with highly complex geometric structure. One important application of complex fine-scale geometric …
ACM SIGGRAPH 2020
PDF Supplement Video

X-Shell Pavilion: A Deployable Elastic Rod Structure

Our first-prize-winning pavilion for the IASS 2019 Pavilion Competition.
Florin Isvoranu, Julian Panetta, Tian Chen, Etienne Bouleau, Mark Pauly
Proceedings of the IASS Annual Symposium 2019 — Structural Membranes 2019
PDF Poster

X-Shells: A New Class of Deployable Beam Structures

X-Shells are a new class of deployable structures formed by an ensemble of elastic beams coupled by rotational joints.
Julian Panetta, Mina Konaković-Luković, Florin Isvoranu, Etienne Bouleau, Mark Pauly
ACM SIGGRAPH 2019
PDF Supplement Code Poster

Rapid Deployment of Curved Surfaces via Programmable Auxetics

We program curved surfaces into flat sheets by optimizing a strain-limited auxetic metamaterial.
ACM SIGGRAPH 2018
PDF Video

Worst-Case Stress Relief for Microstructures

We introduce an efficient worst-case analysis for periodic microstructures and use it to design robust microstructures.
Julian Panetta, Abtin Rahimian, Denis Zorin
ACM SIGGRAPH 2017
PDF Supplement

Thesis: Fine-scale Structure Design for 3D Printing

My thesis develops tools for designing and analyzing objects that leverage the flexibility and resolution of 3D printing.
Julian Panetta
NYU Thesis
PDF

Fine-Scale Structure Design

This poster summaries our Elastic Textures paper and ongoing work on worst-case stress minimization.
Symposium on Computational Fabrication 2016 (Poster)
Poster

Elastic Textures for Additive Fabrication

We design 3D-printable elastic metamaterials and use them to create deformable objects with single-material printers.
ACM SIGGRAPH 2015   –   *Joint First Authors
PDF Supplement Video

Worst-Case Structural Analysis

We introduce an efficient formulation for performing worst-case stress analysis (stress analysis for unknown loads).
Qingnan Zhou, Julian Panetta, Denis Zorin
ACM SIGGRAPH 2013
PDF Supplement

Volumetric Basis Reduction for Global Seamless Parameterization of Meshes

We present an efficient method for generating seamless global parameterizations of meshes with millions of triangles.
Julian Panetta, Michael Kazhdan, Denis Zorin
Technical Report 2012
PDF Supplement

Dynamic Landmarking for Surface Feature Identification and Change Detection

Given the large volume of images being sent back from remote spacecraft, there is a need for automated analysis techniques that can quickly identify interesting features in those images. Feature …
Kiri Wagstaff, Julian Panetta, Adnan Ansar, Ronald Greeley, Mary Pendleton Hoffer, Melissa Bunte, Norbert Schörghofer
ACM TIST 2012
PDF

Change Detection in Mars Orbital Images Using Dynamic Landmarking

As of December 2009, there are more than 1,500,000 orbital images of Mars available on the Planetary Data System’s Imaging Node (from Mars Odyssey, Mars Express, Mars Global Surveyor, and Mars …
Kiri Wagstaff, Julian Panetta, Adnan Ansar, Melissa Bunte, Ronald Greeley, Mary Pendleton Hoffer, Norbert Schörghofer
41st Lunar and Planetary Science Conference, March 2010
PDF

Automatic Landmark Identification in Mars Orbital Imagery

We have developed new methods for automatically identifying landmarks such as craters, gullies, dark slope streaks, and dust devil tracks in remote sensing imagery. These methods are based on …
Kiri Wagstaff, Julian Panetta, Ronald Greeley, Norbert Schörghofer, Melissa Bunte, Mary Pendleton Hoffer, Adnan Ansar
American Geophysical Union, December 2008

Code

VoxelFEM

C++ library for high-performance topology optimization.

Inflatables

Simulation and inverse design for surface-based inflatables.

MeshFEM

C++ finite element library and mesh data structure.

ElasticRods

C++ simulation framework for elastic rods and X-Shells.

RotationOptimization

C++ library for optimizing with rotation variables.

Notes

Structural Analysis with Discrete Elastic Rods

Expressions for the stresses experienced by a discrete elastic rod and discussion of the forces/torques on X-Shell rivets.
Aug 23, 2019

Analytic Eigensystems for Isotropic Membrane Energies

This technical report derives analytical expressions for the eigenvalues and eigenmatrices of an isotropic membrane energy density.
Aug 8, 2019

Optimizing over Rotations

Gradients and Hessians for optimizing with rotation variables.
Nov 5, 2018

Planar Elastica

Analytical expression for the shape of a beam compressed at each end.
Oct 29, 2018

Derivative of the Polar Decomposition

Derives an expression for the derivative of the rotation and stretching part of the polar decomposition.
Jul 5, 2018

Material Derivative of Mean Curvature

Calculation of the material derivative of mean/summed curvature as a surface is advected by some velocity field.
Feb 6, 2018

"Local-Global" Material Optimization

Discussion and analysis of our Elastic Textures paper’s material optimization algorithm.
Sep 1, 2015

Polar Decomposition and the Closest Rotation

Derivation of the closest rotation matrix (in Frobenius norm) to a square matrix.
Feb 23, 2015

Topics

Auxetic metamaterials Change Detection Deployable structures Elasticity FEM Gridshells Homogenization Image Analysis Inflatables Inverse Design Machine learning Material optimization Metamaterials Multigrid Optimization Rods Shape-morphing structures Simulation Topology optimization Worst-case Analysis