CDFAM Computational Design Symposium

Duann Scott
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CDFAM Computational Design Symposium Presentation Recordings www.designforam.com

  1. 2 天前

    Real-Time Computer-Aided Optimization (CAO): How GPU-Native CFD Changes the Industry - Flexcompute - Gregory Roberts

    Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ Organization: Flexcompute Presenter: Gregory Roberts + Qiqi Wang Real-Time Computer-Aided Optimization (CAO): How GPU-Native CFD Changes the Industry Presentation Abstract Computer-aided engineering (CAE) has been a foundational tool in aerospace and photonics design, but slow workflows, high costs, and constrained design exploration limit its potential. Traditional methods rely heavily on intuition and a few simulations to validate designs, leaving vast opportunities untapped. However, a paradigm shift is underway: integrating mathematical optimization techniques like adjoint optimization and inverse design into CAE is redefining what’s possible in engineering. This modern approach – Computer-Aided Optimization (CAO) – directly leverages advanced mathematical optimization to automate and enhance the design process. CAO replaces intuition-driven, validation-focused methods with a data-driven, goal-oriented workflow by specifying design goals and using algorithms to refine configurations iteratively. Techniques like inverse design, which uses objective functions and gradient-based optimization, and adjoint methods, which enable efficient sensitivity analysis, are central to this transformation. GPU-native simulations amplify the impact of these methodologies, making it feasible to address industry-scale problems in a fraction of the time previously required. High-performance GPU computing accelerates the iterative optimization process, enabling rapid exploration of vast design spaces with unprecedented fidelity. Applications range from optimizing aerodynamic performance in aerospace to creating innovative photonic devices like metalenses and quantum computing components. This synergy of mathematical optimization and GPU acceleration positions CAO as the future of engineering design. By reducing costs, accelerating development cycles, and enabling robust design exploration, CAO allows engineers to confidently tackle complex challenges. Whether designing aircraft or photonic circuits, these advancements fundamentally reshape how industries approach innovation, driving breakthroughs across disciplines and unlocking new possibilities for high-performance, efficient design. Speaker Bio Greg Roberts is a research scientist at Flexcompute working on building gradient-based inverse design tools for photonic optimizations. He earned his PhD from Caltech in August 2023 on this same topic. His dissertation focused on the inverse design of 3-dimensional structures for advanced and high efficiency mid-infrared imaging applications. By using gradient information, he demonstrated practical design of color and polarization sorting devices that could be tiled on the pixels of focal plane arrays. Using multilayer fabrication via a finely tuned two photon lithography process, he was able to measure these novel devices to confirm their complex, target behavior. Greg followed graduate school with a postdoctoral research role at NYU applying inverse design to enhance contrast in biomedical imaging. Before graduate school, Greg worked as an embedded software engineer at an augmented reality startup called Magic Leap. Here, he optimized computer vision and machine learning algorithms to run at high speeds on a low-power embedded processor. 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

    21 分鐘

  2. 3 天前

    Assembly Configuration Spaces - C-Infinity - Sai Nelaturi

    Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ Organization: C-Infinity Presenter: Sai Nelaturi Assembly Configuration Spaces Presentation Abstract All non-trivial hardware products are assembled. They are also designed and manufactured in multiple configurations to serve diverse customer needs. Product designs define a configuration space of options that can be instantiated into variants per customer order. OEMs seek to maximize reuse of subassemblies across this space to balance flexibility with cost efficiency—especially in high-mix, low-volume manufacturing. The challenge is translating a product’s design structure into its assembly process structure: reframing design intent as a sequence of operations executed on the factory floor. In Product Lifecycle Management (PLM) terms, this is the translation from the Engineering Bill of Materials (EBOM, “as-designed”) to the Manufacturing Bill of Materials (MBOM, “as-planned”). EBOM and MBOM are not separate domains, but dual representations of the same configuration. Today this translation is manual and painful. At C-Infinity we are automating this translation and building assembly configuration spaces as a foundation for product design and manufacturing planning. By treating EBOM and MBOM as dual views of one structured space, we strengthen reuse, change propagation, streamline configuration management, and enable tighter digital-to-physical integration—addressing long-standing challenges at the heart of advanced manufacturing competitiveness. Speaker Bio Ph.D. Mechanical Engineering, UW-Madison. Expert in CAD, AI, and Digital Manufacturing. Former R&D Director at Carbon and PARC. DARPA and UW career award recipient. 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

    20 分鐘

  3. 6 天前

    Podium Performance: The Future is Personal - Andrew Sink - Carbon3D

    Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ Organization Carbon Presenter: Andrew Sink Podium Performance: The Future is Personal Presentation Abstract In this presentation, learn how world-renowned saddle manufacturer, fizik, has embraced the latest in computational design, customization automation and advanced manufacturing to offer cyclists– from amateur to elite– a one-of-a-kind 3d printed saddle, tuned to their specific needs. The One-to-One saddle leverages each partner’s expertise– fizik’s dedication to saddle craftsmanship, Carbon’s groundbreaking lattice design automation and printing technology, and gebioMized’s dynamic pressure mapping precision– to create a saddle that is not only tuned to custom to each rider, but is also fit for champions. In 2025, Tadej Pogačar rode victorious over the Tour de France finish line on a fully custom One-to-One saddle. But podium performance isn’t achieved overnight. In this presentation, we’ll share how we worked to identify the base saddle geometry, developed robust stress testing, and built a custom pipeline to produce this groundbreaking custom bike saddle at scale. Speaker Bio Andrew Sink is a Senior Applications Engineer at Carbon and is currently focused on enabling companies to create the next generation of production 3D printed parts at scale. An enthusiastic voice in the additive manufacturing industry, Andrew is always excited to talk about what the future holds for this technology. In addition to his work at Carbon, Andrew has written and published software tools that are designed for home and hobbyist 3D printing as well as various technical guides and videos related to additive manufacturing. After graduating from the University of South Florida with a degree in Technical Communications, Andrew has had feature articles published in traditional print media and has also created a YouTube channel focused on 3D printing that currently has a view count of over 9.5 million. 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

    17 分鐘

  4. 11月17日

    Running Revolution: Computational Design Behind Fast-R NITRO Elite 3- Moon Rabbit Lab X PUMA - Jesus Marini Parissi

    Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ Organization Moon Rabbit Lab X PUMA Presenter: Jesus Marini Parissi Running Revolution: Computational Design Behind Fast-R NITRO Elite 3 Presentation Abstract The Fast-R NITROTM Elite 3 marks a true performance revolution, combining cutting-edge engineering with data-driven design. As part of the Collaboration with PUMA, Moon Rabbit Lab developed a computational design workflow that integrates digital simulation, biomechanical analysis and advanced optimization techniques that combined different KPI’s of the shoe’s performance before the first prototype was even made. By running several virtual iterations and hundreds of simulation hours, we achieved a 30 % weight reduction alongside a 3.15 % improvement in running economy versus the previous model, gains that translate directly into seconds shaved off personal bests. This approach unites creative engineering, deep knowledge in material science and targeted biomechanical data, with computational design as the central force driving each decision. This case study highlights the power of combining different areas of expertise with computational design at its core. By prioritizing digital testing and optimization, the process reduces errors and minimizes the need for physical prototyping. Beyond footwear, this scalable framework has broad potential across athletic performance products and a wider range of data-driven consumer goods. Speaker Bio Jesus Marini Parissi is a computational design engineer who merges creative design with advanced engineering methods. He holds a MSc (Master of Science) of Design Engineering from Politecnico di Milano and BSc (Bachelor of Science) in Mechatronics Engineering from Universidad Nacional Autonoma de Mexico, and his portfolio spans performance engineering, consumer goods, automotive product development, and experimental research. He has contributed to global innovation programs like Stanford ME310 and the MIT Design Lab, and worked at Ford Motor Company, earning four patents. He also consulted for brands such as PUMA and Samsung Research America, helping to establish their first Computational Design department. Today, he leads Moon Rabbit Lab, pioneering new frontiers in product development, system optimization, and design research. By fusing imagination with technical expertise, he fosters collaborative innovation and shapes the future of computational design. 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

    18 分鐘

  5. 11月13日

    Intelligent Anatomic Models from CT Utilizing ML - Matt Shomper - Not a Robot

    Organization: Not a Robot Presenter: Matt Shomper Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ Intelligent Anatomic Models from CT Utilizing ML Presentation Abstract This presentation discusses an accessible system that takes CT scans and automatically turns them into detailed 3D models while intelligently tagging important anatomical features. Instead of engineers and researchers spending hours manually creating these models and identifying landmarks, our approach uses machine learning to do the heavy lifting. The process works by feeding CT scan data through specialized algorithms that can recognize the structures and convert the flat scan slices into three-dimensional representations. At the same time, the system automatically identifies and labels key anatomical points like bone structures or tissue edges – creating a smart, annotated 3D map of what was scanned. This has the ability to dramatically speed up workflows that previously required tedious manual work. The automated tagging means that medical professionals get consistent, standardized labels across different cases, which is especially valuable for surgical planning and patient-specific implants. The presentation will cover some challenges of utilizing M/L, how manual inputs can train algorithms over time, and looking towards the future of validating such systems for true use in commercialized systems. Speaker Bio Matthew is a visionary leader in the computational design of advanced 3D-printed medical implants, with close to 15 years of experience in engineering, research, and innovation. As an inventor, creator, and passionate leader, he has been a part of founding businesses focused on additive manufacturing and is an internationally recognized speaker on biomimicry, computational modeling, and additive manufacturing – lecturing at conferences and prestigious universities including MIT and Harvard. Matthew’s work is driven by his passion for exploring the macro and micro of biological forms, turning algorithms into functional structures for physical devices. He has pioneered the idea of a “biologically advantageous implant,” and has also spearheaded multiple public initiatives to synthesize biological structures as computational models for use in engineered products. He currently is the founder and principal consultant of Not a Robot Engineering, a co-founder of LatticeRobot, and involved in several other stealth startups. 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

    17 分鐘

  6. 11月12日

    AI and the Battle for the Soul of Design - Chris McComb - Carnegie Mellon University

    Organization: Carnegie Mellon University Presenter: Chris McComb Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ AI and the Battle for the Soul of Design Presentation Abstract Artificial intelligence is reshaping the landscape of design and additive manufacturing, accelerating creative workflows while challenging long-held assumptions about authorship, originality, and human intuition. As AI becomes more deeply embedded in computational design tools, it offers unprecedented capabilities for exploration, optimization, and customization—often revealing solutions that elude traditional design methods. Yet this power comes with profound questions: What does it mean to design when machines generate ideas? How do we preserve the human element in a process increasingly influenced by algorithmic reasoning? This presentation examines emerging patterns in AI-driven design, the shifting role of the designer, and the ethical dilemmas that arise when intelligence—natural and artificial—co-create. Through examples from additive manufacturing and beyond, it offers a vision for navigating this new design frontier without losing sight of the creative soul at its core. Speaker Bio Chris McComb is the Gerard G. Elia Associate Professor of Mechanical Engineering at Carnegie Mellon University. His lab, the Design Research Collective, advances interdisciplinary design research by merging perspectives from engineering, manufacturing, psychology, and computer science. He also serves as the Director of the Human+AI Design Initiative, an interdisciplinary and international group of researchers focused on application of human-AI collaboration to design, with support by industry partners. He is affiliated with the NextManufacturing Center, the Manufacturing Future Institute, and the Wilton E. Scott Institute for Energy Innovation. His research interests include human social systems in design and engineering; machine learning for engineering design; human-AI collaboration and teaming; computation for advanced manufacturing; and STEM education. He received dual B.S. degrees in civil and mechanical engineering from California State University-Fresno. He later attended Carnegie Mellon University as a National Science Foundation Graduate Research Fellow, where he obtained his M.S. and Ph.D. in mechanical engineering. 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

    20 分鐘

  7. 11月12日

    Design as Dialogue: Form Jamming with AI Agents - Matthew Goldsberry & Junling Zhuang - HDR

    Organization HDR Inc Presenters: Matthew Goldsberry & Junling Zhuang Recorded at CDFAM Computational Design Symposium, NYC, October 29-30, 2025https://cdfam.com/nyc-2025/ Presentation Abstract While AI is often used for visualization in architecture, its potential to directly generate and shape geometry within the design process is still emerging. This presentation explores how we have been integrating model-aware AI agents into our design process. We begin with Synthesizer, a custom browser-based modeling tool paired with an Arduino-powered physical controller. Through a simple physical controller, designers trigger higher-order parametric actions, making the act of modeling feel more performative than procedural. Our early beta experiments, focused on building minimal, controller-driven interfaces, explore new possibilities beyond the traditional mouse and keyboard. We then introduce Form Jamming, a method developed within our RhinoMCP workflow. It treats the initial burst of AI-generated geometry as provisional material—something to be shaped and refined into architecture through intentional, iterative moves. While still experimental, this approach has shown promising results in several recent projects, a few of which we will share. This work outlines a new model of computational authorship in which designers and AI agents collaborate through structured dialogue. It points toward a future where generative design is not only more contextual and adaptive but also legible, editable, and deeply integrated into the design process through natural language interaction. Speaker Bio Matthew GoldsberryMatt oversees the applied research and implementation of advanced computational design workflows. He is the director of Data-Driven Design and is responsible for developing new computational tools and workflows to facilitate design exploration, automated analysis, and advanced data management. Matt is also a Lecturer at the University of Nebraska-Lincoln, where he teaches courses on advanced geometry and building information modeling. Matt holds a Master of Architecture degree from the University of California Los Angeles and a Bachelor of Science in Architecture degree from the University of Nebraska-Lincoln. Junling ZhuangJunling is a design technologist bridging research and practice in the AEC industry. As a software engineer at HDR’s Data-Driven Design team, he develops AI-powered 3D tools. Junling holds an M.S. in Computational Design from Columbia and is pursuing an M.S. in Computer Science at Georgia Tech. His work has appeared in ACADIA and CAADRIA, and he reviews for top venues including ACADIA, CAADRIA, TAD, and FoA 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

    22 分鐘

  8. 11月11日

    Superintelligence for Scientific Discovery in the Material World - Markus J. Buehler - MIT

    We open Season 5 of the CDFAM podcast with a keynote presentation from the CDFAM Computational Design Symposium NYC 2025 by Markus J. Buehler, McAfee Professor of Engineering at MIT. In this session, Buehler outlines how AI is becoming an autonomous partner in scientific discovery—capable not only of analysis but of generating new knowledge. Drawing on examples from materials science and bioengineering, he presents multi-agent AI systems designed to reason, hypothesize, and evolve—creating a framework for discovery engines that extend the boundaries of human-led research. Buehler’s work brings together reinforcement learning, graph-based reasoning, and physics-informed generative models, with case studies showing applications in medicine, food, agriculture, and beyond. Organization: MIT Presenter: Markus J. Buehler McAfee Professor of EngineeringMassachusetts Institute of Technology Presentation Abstract AI is rapidly transitioning from a passive analytical assistant to an active, self-improving partner in scientific discovery. In the material world, this shift means developing systems that not only recognize patterns but also reason, hypothesize, and autonomously explore new ideas for design, discovery and manufacturing. This talk presents emerging approaches toward ‘superintelligent’ discovery engines -integrating reinforcement learning, graph-based reasoning, and physics-informed neural architectures with generative models capable of cross-domain synthesis. We explore multi-agent systems inspired by collective intelligence in nature, enabling continuous self-evolution as they solve problems. Case studies from materials science, engineering and biology illustrate how these systems can uncover hidden structure-property relationships, design novel materials, and accelerate innovations in medicine, food, and agriculture. These advances chart a path toward AI that actively expands the boundaries of human knowledge in engineering. Speaker Bio Markus J. Buehler is the McAfee Professor of Engineering at MIT and a pioneer in AI‑driven knowledge discovery. He created powerful graph‑aware, multi‑agent AI platforms that turn heterogeneous data into science-grounded actionable insight, powering breakthroughs in materials science, biology and healthcare. Buehler is among the world’s most‑cited materials scientists and the recipient of numerous honors, including the Feynman Prize, ASME Drucker Medal, J. R. Rice Medal, and the Washington Award. He is a member of the U.S. National Academy of Engineering. For more than a decade he has also taught executive and technical professionals at MIT, shaping the next generation of leaders in engineering, knowledge discovery, and artificial intelligence. 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

    30 分鐘
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CDFAM Computational Design Symposium Presentation Recordings www.designforam.com

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