CDFAM Computational Design Symposium — Barcelona 2026

Michele Pescatore, Carol Fanjul · AiA Life Designers

Michele Pescatore and Carol Fanjul of AiA Life Designers present a simulation-driven workflow that brings environmental analysis into the earliest stages of architectural design, where decisions have the greatest influence on a project's environmental performance but actionable feedback is usually missing.

Conventional environmental tools require detailed BIM models or expert-level parametrization, so studies become outdated as a project evolves. To close that gap, AiA Life Designers built a streamlined Revit plug-in using Rhino.Inside.Revit, Grasshopper, and the open-source Honeybee and Ladybug ecosystems. It delivers simplified but meaningful indicators directly in the architect's working environment: envelope performance checks, site permeability, carbon impact estimates, and solar and daylight analyses.

The result is real-time, performance-based feedback that lets architects test assumptions, adjust parameters, and see environmental implications well before formal engineering studies begin, without disrupting existing design processes. The presentation covers real-world project case studies, concrete outcomes, and the scalability of these tools across a large architectural organization.

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CDFAM Computational Design Symposium — Barcelona 2026

Verena Vogler · McNeel Europe

Verena Vogler introduces Rhino.Ecologic, an ecological simulation framework for Rhino and Grasshopper built for landscape architects and urban planners working in computational design. The plugin integrates ecological simulation into existing 3D modeling workflows to support nature-inclusive strategies at large and small scales.

The presentation covers how the tool generates location and time specific 3D species distribution maps alongside biomass and biodiversity simulations, supporting data-driven ecological decisions throughout the design process. It includes an overview of the plugin, an introduction to ecological simulation in AEC, and a demonstration of the tool in practice.

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CDFAM Computational Design Symposium — Barcelona 2026

Mary Baker · Palace 3D

Computational geometry has advanced considerably. Color and texture in additive design have not kept pace. As multi-material hardware and capable file formats become more accessible, programming color and texture directly into the design workflow is emerging as a meaningful new capability.

Mary Baker draws on her experience building out that toolset at Palace 3D and previously at HP Inc., covering effects that traditional modeling tools cannot easily produce:

- Embedded data: hidden messages and encoded information within a part's surface

- Gradient control: geometry-driven color and texture transitions

- Realistic in-workflow rendering: accurate as-printed color and texture previews

- Procedural customization: automated generation of unique colorways across product families, including AI-generated content

The session also covers the workflows required to translate digital intent into reliable physical output, common failure points, and how to navigate them.

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CDFAM Computational Design Symposium — Barcelona 2026

Oluwaseyi Sosanya · Gravity Sketch

Spatial computing is regularly framed as a future breakthrough. In certain workflows, it is already delivering measurable value.

Oluwaseyi Sosanya examines where immersive technologies are making a tangible impact in product development today, with particular attention to cable harnessing and automotive clay modeling. These are workflows where teams still depend on physical prototypes to evaluate critical decisions. Spatial tools enable earlier, more confident decision-making by improving spatial understanding and reducing costly physical iteration.

The talk also addresses the practical realities of building for spatial hardware: performance constraints, interaction design, and what it takes to make these systems function in real-world engineering environments.

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CDFAM Computational Design Symposium — Barcelona 2026

Rebeka Melber · Istari Digital

AI coding tools didn't just accelerate software development — they changed who gets to build. A comparable shift is underway in hardware.

Rebeka Melber examines how AI paired with connected engineering infrastructure is lowering the barrier to hardware innovation. The argument isn't that AI replaces deep expertise. It's that it expands who can contribute meaningfully to the design process — and earlier in it. When more of the right people can engage at the right time, ideas move faster and better solutions emerge from places they otherwise wouldn't.

The talk draws on Istari's work with defense and government programs adopting next-generation digital engineering environments, and addresses what it takes to make advanced tools genuinely accessible within complex, mission-critical organizations.

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CDFAM Computational Design Symposium — Barcelona 2026

Javier Blanco Cordero · Quix

Engineering teams have found AI useful for discrete tasks: SQL queries, graphs, summaries. Higher-value work, root cause analysis, physics-based ML, production deployment, remains out of reach. The standard diagnosis is that the models need to improve. Javier Blanco Cordero's experience points the other way: the models are already sufficient. The infrastructure surrounding them is not.

Using a real rotor balancing case involving 50,000 rotors per year, this talk walks through what it takes to move AI from task-level support to autonomous engineering investigation. With the right infrastructure in place, a model that had underperformed on summary data identified a discriminating signal in 100 kHz vibration data that decades of domain expertise had missed. That same model independently designed a deployment plan that reduced total balancing runs by 41%.

The presentation covers what was built, the results, and what it means for any organization sitting on complex engineering data.

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Quercus Hernández · Emmi AI

Recorded at the CDFAM Computational Design Symposium, Barcelona 2026.

In this episode

Presentation Abstract

Engineering is entering a new paradigm where AI is no longer limited to accelerating isolated simulations, but is becoming a foundational layer of the industrial design and manufacturing stack. Across sectors such as automotive, energy, semiconductors, and aerospace, engineering workflows remain constrained by slow simulation feedback loops, fragmented CAD-to-CAE pipelines, and computational bottlenecks that limit design exploration and innovation speed.

In this talk, we present the vision of Large Engineering Models developed at Emmi AI: physics-aware foundation models designed to operate directly on industrial geometry and process inputs while replacing large parts of the traditional numerical simulation workflow. Rather than focusing on narrow surrogate models, this approach consolidates geometry processing, physics prediction, and post-processing into a unified AI-native engineering interface that provides near real-time feedback to engineers and designers.

As a concrete industry showcase, we present NeuralMould, our first commercially deployed Large Engineering Model for injection moulding. The model enables engineers to evaluate design changes such as gate placement, material selection, and process parameters with near-instant feedback, eliminating traditional meshing bottlenecks and dramatically accelerating design iteration cycles. In addition, we introduce Noether, our recently released open-source framework for building and deploying engineering AI models at scale. Noether provides the infrastructure for training, fine-tuning, and operating Large Engineering Models across domains, enabling industrial partners and researchers to develop their own AI-native simulation capabilities.

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Beyond Parametric: Explorable Simulation for Real Design Iterations

Presentation Abstract

Design space exploration promises engineers the ability to evaluate thousands of variants in hours. The prerequisite—rarely discussed—is building a parametric geometry model that won’t break. This front-loaded investment assumes you know your design space before exploring it. Real engineering iteration isn’t parametric. Design changes are structural and topological: fundamentally different geometries evaluated against the same performance criteria.

Setup time, not simulation time, is the real bottleneck in enabling simulation-driven exploration for real engineering teams.

At Generative Engineering, this is what we are addressing. We enable explorable simulations that work with both parametric exploration and novel designs. We will demonstrate how this is unlocked by using existing simulation data inside engineering organisations to train geometry preparation models rather than physics surrogates.

This lets the messy, collaborative, real design iterations be simulated with zero setup cost. But the same principle extends further: if a model understands what makes geometry simulation-ready for a given analysis, it can generate that geometry directly. We’ll show work on closing this loop—from a sketch or annotation on a previous design to simulation-ready geometry, collapsing the traditional boundary between design intent and engineering validation.

Speaker Bio

Laurence Cook is Co-Founder and Chief Product Officer at Generative Engineering.

After academic work at MIT, Stanford, and Cambridge, Laurence brought his computational engineering to the commercial industry and is now leading the initial commercial product of Generative Engineering. A 20 strong team of computational and commercial experts who have currently raised €13m.

Deterministic engineering analysis assigns fixed values to loading conditions, geometry, and material properties. The approach is tractable, but it forces a choice between conservative overdesign and exposure to failure modes that fall outside assumed limits. Neither outcome is satisfying.

Greg Grigoriadis of Metisec describes a design toolkit that replaces fixed inputs with statistical distributions and runs Monte Carlo simulations across the resulting parameter space. The output is a probabilistic picture of performance: failure probabilities, sensitivity rankings, and the specific conditions that actually drive risk.

A sensor mounting bracket for a smart wearable serves as the test case. Traditional optimization cut bracket weight by 30%. Probabilistic analysis revealed the design had been tuned to an improbable drop event and still carried unresolved thermal failure risk. Incorporating that information allowed the team to re-optimize and achieve a 50% weight reduction at a demonstrably low failure probability.

Greg is an engineering consultant specializing in consumer electronics, digital twin technologies, and advanced simulation workflows. His practice combines physics-based modeling with data-driven methods across finite element analysis, predictive maintenance, and automated computation pipelines.

Presented at CDFAM Barcelona 2026. Learn more at cdfam.com.

Body-in-White development sits at the intersection of structural performance, manufacturability, and schedule pressure — and traditional workflows are increasingly strained by the pace of platform proliferation and regulatory demands. This episode examines how SEAT/CUPRA is modernizing BIW development through Synera’s Multi-Agent System (MAS), connecting CAD, CAE, and manufacturing processes within a unified automation framework to accelerate iteration and improve engineering traceability.

Tilman Steininger, Customer Success Manager for Agentic Engineering at Synera, and Juan De Dios Escribano Felguera, Team Lead for Body-in-White and Corrosion Development at SEAT/CUPRA, present their collaborative work digitizing structural development workflows across the full BIW development cycle. Recorded at CDFAM Barcelona 2026.

About CDFAM

The CDFAM Computational Design Symposium is a global conference series bringing together researchers, engineers, and software developers working at the intersection of computational design, AI and machine learning for engineering and architecture. The program spans computational geometry, generative design, topology optimization, simulation-driven workflows, and advanced manufacturing across scales from architected materials to architectural systems. CDFAM events are held worldwide.

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