CDFAM Computational Design Symposium

CDFAM Computational Design Symposium — Tokyo 2026George Allen · nTopBy now, implicit modeling technology and its benefits are well understood. In situations where a part is highly complex or its design process is highly iterative, implicit modeling using signed distance fields is uniquely able to deliver the reliability, performance, and scalability that are required for success. However, the novelty of implicit modeling is also a source of problems. Current engineering/manufacturing processes are often heavily dependent on legacy software tools that cannot consume implicit models — they require meshes or boundary representations, instead. So how do we address this problem? There are a few options — we can either convert implicit models to the forms needed by legacy tools, replace the legacy tools with new ones that consume implicit models directly, or change the data flow in the overall process. The talk examines these issues, reports progress and the current status, and suggests some ways forward.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — Tokyo 2026Darren Henry · PTCThe race toward AI-generated CAD has largely focused on teaching models to produce geometry directly—from B-reps and meshes to feature histories and sketches. But what if we’re teaching AI the wrong language?This presentation explores an alternative paradigm: Text-to-Code-to-CAD, where large language models generate engineering logic rather than geometry itself. Instead of predicting low-level geometric entities, AI writes executable CAD code that captures design intent, constraints, parameters, and engineering relationships. The result is not merely a finished model, but a native, editable, and reusable engineering feature that integrates naturally into the design workflow.Using real-world examples, including AI-generated CAD features built through FeatureScript, this session demonstrates how modern language models can write, test, debug, and refine engineering code to create complex parametric designs while preserving the transparency and editability required for professional engineering. The discussion contrasts this approach with direct geometry generation and examines why engineering intent—not geometry—may be the more scalable representation for AI-assisted design.Attendees will leave with a new perspective on computational design: the future may not be AI replacing CAD, but AI leveraging programming languages purpose-built for engineering to accelerate design while keeping engineers firmly in control.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — Tokyo 2026Matt Sederberg; Dr. Michael Scott · CoreformMatt Sederberg and Dr. Michael Scott of Coreform present isogeometric analysis (IGA) as a route to simulating directly on CAD geometry, and outline a mathematical framework for running multi-agent LLM workflows in high-assurance engineering domains.Sederberg covers the background of IGA, introduced by Tom Hughes and now the subject of more than 7,000 research papers, and its recent integration into Abaqus through a partnership with Dassault Systèmes. In one example, a brake caliper that took 20 hours to defeature and hex mesh, with critical fillets removed, was ready to solve in under a minute with full CAD geometry intact. With no meshing step, an agent can change the design, rerun the analysis and read the results without a human repairing the mesh in between.Scott then previews Coreform AI, built on four concepts:IGA as a robust physics solver for agent-driven workflowsA data weave, an algebraic relational representation that lets agents query all simulation pipeline data at roughly constant token cost, regardless of data sizeSupport for smaller, controllable and air-gapped models, demonstrated with Claude Haiku reaching the same result as larger modelsAgent coordination posed as an energy minimization problem using game theory, with market mechanisms that penalize agents for false completion claimsHe also describes formally verifying the underlying software in Lean, with more than 6,000 theorems backing returned results.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — Tokyo 2026David Burpee · MorphXgenMany Additive footwear platforms promise a level of customization beyond traditional footwear manufacturing processes, but how custom is it really? This presentation will explore a variety of strategies for the integration of various custom data into bespoke additive-ready algorithms in footwear design. The ability to create force-responsive structures through various types of micro lattice to tune flexibility, gradient behavior, anisotropy all within the confines of additive manufacturability parameters. Approaches include multi-agent algorithms with intelligent emergent behavior, simulation-driven anisotropic stochastic lattice structures, and body-responsive data mapping for truly one-of-one additive footwear creations.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — Tokyo 2026Sarat Babu · SARATComputational design approaches to optimization are often constrained by the tools available and the established methods for generating optimal forms. With AI coding tools, the barrier for designers to develop their own software and pipelines has dropped considerably.Sub-Optimal reframes optimization around two priorities: preserving the original designer’s macro intent, and using geometry to address the anisotropic surface roughness of additive manufacturing. The result is neither lattice application nor topology optimization, but a grown internal structure driven by simulation, surface texture and build orientation that remains largely invisible at the macro level.The talk covers the trust gap senior engineers face with optimized DfAM parts, the use of surface texture to mask layering defects and build orientation, and how the pipeline was built in six weeks for about $400 in AI tokens using open-source libraries including geometry3Sharp and OpenVDB, with 3MF as the output format.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — Tokyo 2026This episode is the opening keynote from CDFAM Tokyo 2026, presented by Guido Cossu and Ivo Timóteo of Braid.Braid was founded in Tokyo in 2020 by a team drawn from physics, applied mathematics, computational geometry, large-scale simulation and machine learning. At the time, the prevailing view in AI held that scaling end-to-end learning on ever-larger datasets would solve most problems. Braid took a different position: engineering design, where physical accuracy, safety and manufacturability are non-negotiable, requires reasoning from the laws of physics and the constraints of manufacturing rather than pattern-matching from prior examples. Their system, AURA, combines learning with formal reasoning to move from engineering intent to manufacturable geometry, replacing the manual draw, simulate, review and redraw loop with structured exploration of alternatives that the engineer evaluates and selects from.In this talk, Cossu and Timóteo explain the semantic architecture behind that approach and show results from deployments in Japanese manufacturing, across several mass-production processes with little in common.The Best Design Is The Design You Can MakeGuido Cossu; Ivo Timóteo · BraidAcross computational design, the part that performs and the part that can be built are rarely the same part: optimization and generative methods meet the functional targets, and the work of making the result manufacturable happens afterward, by hand, often negating the performance that was gained. Braid closes that gap differently. Rather than optimizing a seed geometry or generating candidates from data, the system designs de novo — geometry reasoned directly from what an engineer specifies: function, physical conditions, the manufacturing process the part must suit, the cost it must meet. The mechanism is semantic reasoning rather than data-driven generation: a semantic architecture encodes physics, geometry, and manufacturing constraints with their relationships, and enforces constraint satisfaction by construction. Because the manufacturing process is reasoned from rather than filtered for, the geometry is manufacturable from the first output, not repaired into manufacturability afterward.Braid demonstrate this on real engineering components across several conventional mass-manufacturing processes, each with its own design constraints. The examples come from deployments in Japanese manufacturing industries where tolerances are tight and errors are costly. One system handling processes with so little in common is the crucial point: each result is reasoned from principle, not retrieved from examples of similar parts — which is, in the end, the difference between a design system you can trust on a novel part and one you can only trust on a familiar one.LinksTalk page with full transcriptWatch the talk on YouTubeInterview with BraidCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — DC 2026Giorgia Cannici · Virginia TechWhat if material fabrication could shift from assembly to growth—and be directed with precision through external fields?This work introduces magnetotropic plants: genetically engineered organisms in which gravity-sensing organelles (statoliths) are rendered magnetically responsive. By replacing gravitational cues with externally applied magnetic fields, plant growth direction can be actively controlled in real time. This enables programmable morphogenesis, where biological growth becomes a steerable process rather than a fixed outcome of genetics and environment.The presentation will outline the biological mechanism, the experimental framework, and the implications of this approach for material production.Magnetic fields act as an invisible, non-contact control layer, allowing spatial and temporal guidance of growth without mechanical intervention.Beyond applications in microgravity environments such as space, this work suggests a broader shift in how we produce materials—moving from extractive, energy-intensive processes toward growth-driven fabrication, where form emerges from the interaction between engineered biology and designed environmental conditions.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — DC 2026Matthew Shomper · Not a Robot EngineeringNature has been solving the problem of impact protection for millennia, in order to arrive at solutions far more elegant than anything on the market today. The microstructure of a bighorn sheep’s horn is one of the most striking examples : a geometry that is brutally efficient at scattering and absorbing energy, such that the animal can sustain repeated high-speed collisions without lasting damage. The challenge has always been translating that geometry into something we can actually manufacture.Additive manufacturing allows us to build internal geometries that were previously impossible to fabricate : graded densities, interlocking fiber patterns, and layered structures that mirror what nature spent millions of years optimizing. By digitally modeling the ram’s horn at the microstructural level and translating those patterns directly into printable designs, we can produce armor components that outperform conventional materials in energy absorption while perfectly conforming to the body.This work represents a broader shift in protective equipment design: away from material selection alone, and toward architecture as the primary engineering tool.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — DC 2026Damola Michael; Elliot Glassman · CannonDesignThe environmental design conversation typically begins too late, after massing is committed and geometry is locked. Aurora repositions that conversation to day one, giving architects and engineers an immediate, evidence-based picture of any site before a design tool is opened.The platform synthesises EPW weather files, CMIP6 climate projections, ASHRAE design conditions, NOAA historical records for US sites, and seismic hazard data into a unified analysis environment, covering temperature and humidity distributions, wind roses, solar radiation by facade orientation, thermal comfort (UTCI, PET, SET), rainfall, carbon intensity, and future projections to 2050. Every analysis is immediately exportable as a formatted PDF or PowerPoint report, ready to present to a client or design team without additional preparation.Two integrated AI layers surface this data as design insight. A streaming conversational assistant powered by Google Gemini is grounded in the actual EPW and CMIP6 data for the active location. It explains what site climate means for design decisions, renders specific charts inside the conversation, and adjusts application settings through natural language. A second layer generates AI-written summary cards for ASHRAE design conditions and 2050 climate outlooks, automatically scoped to the site.Aurora does not generate or evaluate geometry. This is intentional: it is a pre-design climate intelligence layer, not a replacement for tools like Autodesk Forma. It provides the environmental literacy that should inform every decision made in those tools, a shared language between architect, engineer, and client before a single wall is drawn.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com

CDFAM Computational Design Symposium — DC 2026Matthew Sederberg · CoreformThe traditional “design-to-analysis” loop is often bottlenecked by the laborious process of mesh generation, which can consume up to 80% of total simulation time. This presentation introduces Coreform IGA for Abaqus, a solution that brings CAD-exact isogeometric analysis (IGA) directly into the Abaqus ecosystem. By utilizing Coreform’s Isogeometric Analysis approach, users can perform high-fidelity simulations directly on CAD geometry, effectively bypassing the need for traditional finite element meshing.LinksTalk page with full transcriptWatch the talk on YouTubeSearch this talk's transcriptCite this talk This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit www.designforam.com