Julian Marcon

About Julian Marcon

I\'ve spent 10+ years solving the hardest geometry and mesh generation problems in computational engineering — from writing high-order mesh algorithms for NASA aerospace simulations to building the geometry infrastructure powering Physics AI platforms at production scale.My domain sits at the intersection of computational geometry, mesh generation, and high-performance computing. I\'ve worked at the core of open-source simulation frameworks — Nektar++ and NekMesh — contributing algorithms now cited 267+ times across 12 publications. My technical foundation spans spectral/hp element methods, adjoint-based optimization, and high-order curvilinear meshing, with deep hands-on experience in C++, Python, and distributed computing environments.On the business side, I\'ve delivered measurable impact: a routing optimization algorithm at 6 River Systems (a Shopify company) projected to save $10M+ annually, geometry repair pipelines at Luminary achieving 90%+ automated success rates, and a NASA Postdoctoral Program fellowship awarded competitively to advance adjoint mesh methods for aerospace simulation. I report directly to executive leadership and have driven products from beta to GA while mentoring engineers and building the technical foundations others build on.

Experience

1. Computational Meshing Engineer

   Luminary

   Aug 2022 — Present · San Mateo, CA, US

   Led the beta-to-GA transition of Luminary\'s geometry and meshing platform, scaling from prototype to a production system supporting enterprise Physics AI workflows.• Architected the interface between the geometry kernel and the Physics AI system — unifying traditional CAD/meshing infrastructure with AI-driven simulation for both training and inference.• Operated as the full-lifecycle domain owner for geometry workflows in a high-ambiguity startup environment — defining requirements, building solutions, driving UX, and validating with customers across product, engineering, and design without formal role boundaries.• Built real-time CAD processing pipelines with 90%+ automated repair success rates and a geometry tagging system that cut user configuration time by up to 90%.• Designed a multi-kernel geometry processing architecture abstracting ACIS, Parasolid, EGADS, and an in-house discrete kernel — with IOP for cross-kernel CAD interoperability and parametric geometry ingestion from Onshape, ESP/OpenCSM, and Blender — enabling seamless history-based kernel switching and broad file format support.• Served as the primary technical authority for geometry across the organization — advising developers, solutions engineers, customers, and executive leadership.• Mentored 2 junior engineers (a Sutter Hill Ventures Codepoint fellow and a PhD graduate) through full development lifecycles, accelerating project delivery by 6 months.• Recognized with three internal awards — Rigor Award, Hackathon Velocity Award, and Speak Up Award — for technical excellence, rapid prototyping, and cross-functional initiative.

Education

• Imperial College London

  Doctor of Philosophy (PhD) & Diploma of Imperial College (DIC), Aeronautics

• New York Institute of Technology

  Bachelor of Science (B.S.), Mechanical Engineering

• Imperial College London

  Master of Science (MSc) & Diploma of Imperial College (DIC), Advanced Computational Methods

Skills

• Ecosimpro
• Python
• Catia
• Openfoam
• Paraview
• Fine/Open
• Comsol
• Oofelie::Multiphysics
• Matlab
• C++
• Fine/Fsi-Oofelie
• Java
• Samcef Field
• Ptc Creo Parametric
• Fortran