NYC, 2025 Archive
October 29-30, 2025
Archive of recordings of presentations from leading experts in computational design across all scales, from micro to mega in NYC, October 29-30 at NewLab.
From AI and machine learning for material development and simulation, to multi-objective computational design of architectural systems, the two day program features researchers, practitioners and software developers leading the advancement of data-driven design, agnostic of application.
Presentations are released at a cadence of two per week after the event as video on Youtube and audio Podcast. Subscribe for updates to these, and future recordings.
Program
October 29th – 30th, 2025
Organization:
MIT
Presenter:
Markus J. Buehler
McAfee Professor of Engineering
Massachusetts Institute of Technology
Opening Keynote: Superintelligence for scientific discovery in the material world
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.
Presentations
Organization
HDR
Presenter:
Design as Dialogue: Form Jamming with AI Agents
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 Goldsberry
Matt 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 Zhuang
Junling 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
Organization:
Carnegie Mellon University
Presenter:
Chris McComb
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.
Previous Presentation
Organization:
Matt Shomper
Presenter:
Matt Shomper
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.
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.
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.
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.
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
Qiqi Wang: Associate Professor at MIT specializing in computational sciences, chaotic systems, and optimization for aerospace. His pioneering work bridges theoretical research with practical applications in unsteady aerodynamics and exascale computation.
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.
Organization
ToffeeX
Presenter:
Marco Pietropaoli
Design You Can Trust: Explainability and Control in Physics-Driven Generative Design
Presentation Abstract
Generative design can unlock high-performance solutions, but adoption often slows when results appear too complex or unfamiliar. At ToffeeX, we have learned that trust is just as important as performance, especially in industries like aerospace or data center cooling, where explainability is essential.
In this talk, I will share how our vision continues to evolve. Rather than removing the human from the loop, we focus on removing only the human biases that tend to simplify or distort complex physics, especially fluid dynamics, during the early stages of design. Instead, our tools aim to enhance human critical thinking, enabling designers to better interpret and direct physical principles.
With the latest features, unit cell repetition, symmetry, modularity, wedges, and feature size control, applied within manufacturing constraints, users can guide and explore designs optimized at both macro and meso scales, while also appearing familiar, explainable, and trustworthy.
Biases also affect material choices. Engineers often default to metals for their thermal properties, overlooking what well-designed, advection-driven systems can achieve. ToffeeX enables fluid motion to carry the thermal load, allowing plastic parts to outperform metal ones, while being lighter, cheaper, and faster to produce.
Through real-world examples, we will show how these advances improve not just performance and trust, but also speed, accessibility, and integration with modern CAD and CAE tools.
Marco is a mathematician from the University of Rome and the founder of ToffeeX, a deep-tech startup in London focused on generative design. He holds a PhD in optimal design for thermo-fluid systems from Imperial College London and combines a passion for optimisation, shaped by early work on swarm algorithms, uncertainty quantification, with a commitment to physics and human-centered tools.
Organization:
Alloy Enterprises
Presenter:
Ryan O’Hara
Shaping Flow: Computational Design Strategies for High-Performance Liquid Heat Exchangers
Presentation Abstract
At Alloy Enterprises, we combine traditional CAD, implicit geometry modeling, and advanced simulation workflows to engineer high-performance cold plates tailored to the unique thermal and dimensional requirements of each customer. Our approach begins with a curated library of optimized, periodic internal geometries that serve as a foundation for thermal performance and manufacturability. Using computational design tools, we scale and adapt these geometries through parametric controls and implicit modeling techniques, enabling rapid customization across a wide range of form factors. Simulation-driven iteration ensures that each design meets target pressure drop and heat transfer criteria before it reaches the build stage. This integrated workflow allows us to balance design flexibility, performance, and production efficiency in delivering scalable liquid heat exchangers for demanding applications.
Speaker Bio
I am a results-oriented business development leader with over 20 years of DoD acquisition experience. I have extensive experience in advanced manufacturing, aerospace engineering, and federal contracting. I have a proven track record of driving significant revenue growth and securing substantial funding through strategic proposals and federal contracts. With expertise in technical hardware and software sales, I enable cross-functional collaboration in aerospace application development. My technical experience includes transitioning research and development activities from concept to full-scale production, leveraging advanced design and manufacturing concepts. I have demonstrated success in initiating and developing processes, including the certification of materials, equipment, and procedures that comply with aerospace and maritime standards.
Organization:
Novineer
Presenter:
Dr. Ali Tamijani
Simulation and Optimization for FFF/FDM Printed Parts
Presentation Abstract
Additive manufacturing with FFF/FDM 3D printing has long struggled to optimize toolpaths for better structural performance. Traditional slicing software failed to fully take advantage of material anisotropy, missing opportunities to boost strength and stiffness. Novineer’s toolpath optimization software changes this by maximizing material properties through tailored print paths based on load paths, resulting in a 60% increase in structural stiffness without changing the geometry.
Speaker Bio
Dr. Ali Tamijani, the co-founder/CEO of Novineer, is a professor of Aerospace Engineering at ERAU. He has spent three summers at Air Force Research Laboratory (AFRL) as a Faculty Fellow to explore the structural load paths and load flow. This was followed by investigating a Load Path-based Topology Optimization funded by the Air Force Office of Scientific Research (AFOSR)-Young Investigator Program (YIP). Ali is also working on Multiscale Optimization of Additively Manufacturable Cellular Microstructures that received the National Science Foundation (NSF) -CAREER.
Organization
Eaton + Intact Solutions
Presenter:
Karthik Rajan Venkatesan
Neel Kumar
Accelerating Metal-to-Plastic Conversion with AI, Implicit CAD, and Mesh-Free Simulation
Presentation Abstract
This work presents a simulation-driven generative design framework for reengineering a metallic explosion-proof enclosure into a lightweight, injection-molded fiber-reinforced plastic alternative. The methodology integrates advanced process and performance simulations with AI-guided optimization to enable rapid, intelligent design iteration.
Central to this workflow is the use of implicit CAD modeling in nTop, which allows for highly flexible and parameterized geometry generation, seamlessly integrated with a robust, mesh-free simulation engine from Intact Solutions. This combination eliminates traditional meshing bottlenecks and enables direct evaluation of complex geometries without meshing or format conversion.
The workflow is executed in two stages. Stage I establishes baseline using Moldflow for plastic flow simulation, Digimat for fiber orientation mapping, and ABAQUS for traditional FEA, culminating in a stress field point cloud. Stage II transitions to an AI-driven design space exploration loop, where models are trained and evaluated through a Bayesian optimization framework. The implicit CAD models are directly analyzed using Intact.Simulation for Automation without any manual pre-processing, enabling a seamless feedback loop between design and performance while supporting rapid, large-scale design iterations.
This approach exemplifies the power of computational design at scale—reducing turnaround time from over 48 hours with traditional CAD and FEA methods to under 1.5 hours with the full AI-driven pipeline with implicit modeling and automated, mesh-free simulation.
Speaker Bio
Karthik Venkatesan is a Lead Engineer in Computational and Digital Product Development at Eaton’s Center for Materials & Manufacturing Innovation in Southfield, Michigan. His work focuses on bridging advanced simulation, AI, and generative design to accelerate the development of next-generation engineered systems. Karthik leads R&D initiatives that span simulation-driven design automation, lightweighting, and digital workflows for both traditional and additive manufacturing (AM) processes.
He holds a Ph.D. in Mechanical Engineering from Arizona State University, where he led multiscale modeling efforts for composite materials under DoD- and industry-funded programs. His broader research spans geometry compensation for binder jet AM, performance prediction for polymer extrusion-based AM, virtual design of experiments, and generative AI for material discovery.
Karthik is also passionate about computational creativity, with interests spanning astro photography, AI-generated media, and music production
Organization
VARIANT3D
Presenter:
Will Samosir
Knit Everything: Surfaces, Systems, and the Future of Textiles
Presentation Abstract
What if anyone who can draw could knit?
VARIANT3D exists to break down the barriers to textile manufacturing. Our proprietary software LOOP is the first and only WYSIWYG CAD system for knitting that requires zero knowledge about how knitting works.
Unlike conventional knit engineering, which demands months of expert iteration, LOOP lets anyone access a vast library of knit structures and generate machine-ready files in minutes, bringing industrial complexity down to a creative interface. From instant prototyping to scalable product lines, our platform also supports automated calibration and grading. In a world saturated with cut-and-sew fabrics, we’re pioneering a decentralized, on-demand, and zero-waste model of textile production.
Beyond that, we recognize that knitting is a medium that blends the language of computation, powerfully soft and flexible materials, as well as pure, collaborative human ingenuity. At VARIANT3D, we’re not just building tools—we’re also cultivating a new language for textile and material innovation. We are excited to share how this vision has shaped our process and journey as an organization, and how we are empowering the future of textiles.
Speaker Bio
Will Samosir is the CTO and Co-Founder of VARIANT3D, where he champions a future that is expressive, adaptive, sustainable, and open. He leads a multidisciplinary team and spearheaded the development of LOOP, a state-of-the-art software platform that reimagines how textiles are made—and who gets to make them. His life’s work is rooted in the belief that humans and computers are co-authors, and that our relationship with complex systems should be intuitive and human-centered.
Will is also obsessed with computational geometry, topology, generative design, and emergent behavior. His favorite language is Python, and he’s drawn to all things polymorphic—surfaces, materials, tactile stuff, naming systems, myth and mythology, the many languages of art, and how tools shape thought. He loves music and live shows, and if you’re lucky, you might catch him biking through the summer streets of Brooklyn!
Organization:
New Balance
Presenter:
Samuel Whitworth
Computational Craft: One Footwear Designer’s Quest to Replace Himself
Presentation Abstract
Footwear design, like many design domains, has long been defined by the combination of two-dimensional drawings and designers’ intuition. While these remain important elements of the field, various digital design methods are currently surging and have significantly altered the traditional footwear design process. This presentation will explore the opportunities presented by this shift through the lens of my own experience as an industrial designer turned computational designer—specifically how the application of computational methods has allowed me to expand the types of design solutions I can explore. In this sense, it’s been a journey of “replacing” my traditional industrial design role with a new hybrid role defined by what I call “computational craft.”
Computational craft can be defined as a collaborative human/computer design approach, where the computer extends the reach of the human designer, while the human grounds computational results in the real world of manufactured objects and human sensibility. I will demonstrate several examples of this method in Grasshopper, including Kangaroo-based simulations, multi-objective optimization, and mesh generation/manipulation. Audience members will be able to take away new inspiration for using computational methods in their design workflows, and a feeling of confidence that computational design is accessible to anyone regardless of academic or professional background.
Speaker Bio
Samuel Whitworth is a Computational Designer II at New Balance Athletics, where he has contributed to both inline and innovation projects for the past six years (recent releases include the SuperComp Elite v4 and More v5.) Sam focuses on the intersection of footwear geometry and function using scripting, simulation and functional prototyping, leveraging deep skillsets in both Grasshopper and Blender. He holds a Bachelor of Fine Arts in Industrial Design from Brigham Young University.
Organization:
Harman International
Presenter:
Austin Mitchell
Acoustic-Driven Computational Design: Premium Branded Audio in the Automotive Industry
Presentation Abstract
In the evolving landscape of automotive experiences, premium audio has become a defining element of in-cabin experiences and brand identity. At Harman International, we sit at the intersection of acoustic engineering, branded storytelling, and advanced manufacturing—designing audio systems globally for over fifty automotive manufacturers.
This presentation explores how computational design is central to our industrial design strategy, enabling our team to generate highly manufacturable, acoustically-performative designs that are both brand-specific and scalable across diverse vehicle platforms.
This talk will go beyond production work to discuss how computational design fosters entrepreneurship—creating space for designers to prototype new product categories and contribute to IP development.
Speaker Bio
Austin Mitchell is a senior computational designer at Harman International leading acoustic-driven computational design initiatives across automotive and lifestyle industries.
Organization
David Burpee Design
Presenter:
David Burpee
Computational Morphogenesis: Leveraging Proceduralism to Unlock Temporal Design
Presentation Abstract
Current paradigms of design and engineering operate on the premise that realized designs are static – that is once they are designed and manufactured they exist in their final state. Likewise even flexible computational systems tend to not incorporate the dimension of time as a design tool. Despite dozens or hundreds of sliders, variables, and graphs, most products – even those designed computationally – are “frozen” at a certain point and designed as a static object.
New advancements in material science research particularly around Engineered Living Materials or ELMs have elucidated these shortcomings in our design and engineering workflows. How can we model, simulated, validate, product performance or behavior in this dynamic, temporal environment? We need new processes, workflows, methods, and tools in order to effectively utilize this new dimension of material typologies, as well as continue to design in ways that are more connected to engineering simulation and validation.
In this presentation I will explore the use of proceduralism as an essential creation environment that is uniquely able to design in conjunction with these temporal constructs. I will present a subset of my work that utilizes computationally-driven simulations for the creation of physical product, as well as some of my teaching and research through the NSF grant project designing with Engineered Living Materials at the University of Washington.
Speaker Bio
David Burpee is a multidisciplinary Computational Design Leader based in the Pacific Northwest, with expertise spanning Footwear, Apparel, Consumer Goods, Automotive, Medical, and Architecture industries. He lectures on Computational Design and Algorithmic Thinking at the University of Washington and is a Computational Researcher on a National Science Foundation grant exploring Engineered Living Materials (ELMs).
With over a decade of Computational Design experience, David has delivered advanced design strategy, tools, and training for companies including Nike, PUMA, FILA, General Motors, Harry’s Razors, and EQLZ. His work demonstrates a proven methodology that merges creativity, deep technical capabilities, and broad market impact.
Originally trained as an Architectural Designer with a Master of Architecture from USC, David has contributed to highrise and supertall projects in Los Angeles, Seattle, and across Asia. His work integrates computational approaches at every scale, from skyscrapers to small installations.
Driven by a passion for biomimicry, generative systems, and sustainable innovation, David applies computational design to address complex ecological and social challenges through creative, high-performance solutions.
Organization:
NVIDIA
Presenter:
Ian Pegler
Keynote Presentation: How NVIDIA is Accelerating Product Development
Presentation Abstract
Computational simulation and design have transformed product development by significantly reducing time and costs. However, designing complex products remains a challenging and resource-intensive process.
In this presentation, we will explore key industry challenges and demonstrate how NVIDIA is leveraging innovative solutions to address them. Specifically, we will highlight the use of accelerated computing to enable faster, higher-fidelity simulations, and AI surrogate models to provide designers with real-time feedback.
Additionally, we will discuss integrated approaches that combine these technologies to create responsive, real-time digital twins. The foundational platform supporting these advancements will be examined, along with real-world industry applications illustrating their impact.
Speaker Bio
Ian Pegler is a member of the Computer-Aided Engineering (CAE) team at NVIDIA. With a career largely focused on computational fluid dynamics (CFD), Ian has extensive experience across various industries, including aerospace, automotive, energy, and marine. Currently, he collaborates with small and start-up CAE companies to help accelerate their engineering tools and workflows. Ian holds a Master’s degree in Aerospace Engineering from the University of Southampton, UK, and is based in Chicago.
Building Beyond Imagination: How AI-Native Engineering is Rewriting the Rules of Innovation
Presentation Abstract
Engineering is entering a new era. Just as simulation transformed design in the 1990s, AI is now redefining the entire engineering lifecycle — from generative design and multi-physics simulation to process optimization and manufacturing. This talk explores how a truly AI-native engineering tech stack is empowering industries to build beyond human imagination. Moving past narrow surrogates and isolated accelerations, we’ll show how Large Physics and Geometry Models, combined with adaptive workflows, link every stage of innovation into a seamless continuum. Drawing on real-world applications across aerospace, semiconductors, energy, and advanced manufacturing, we’ll demonstrate how this approach compresses months of design iterations into days, enables process breakthroughs once thought unattainable, and vastly expands the boundaries of engineering creativity. The result is not just dramatically faster cycles. It’s a fundamental shift in how engineering is done — where AI doesn’t just simulate or optimize but orchestrates and amplifies human ingenuity to redefine what’s possible.
Speaker Bio
Mark Huntington is the Managing Director of North America at PhysicsX, leading the company’s regional expansion and AI-driven product and process optimization. Based in New York, he focuses on advancing renewable energy, sustainable materials, semiconductors, and the future of aerospace & defense, and automotive. With over a decade in consulting and technology, Mark was previously a Partner at McKinsey & Company, specializing in AI, machine learning, and digital twins. As a core leader at QuantumBlack, he spearheaded high-impact projects for industrial companies, including digital twins for renewable power plants, automotive component optimization, and digital engineering transformations in aerospace & defense. He also led AI-driven strategies for engine manufacturers and autonomous vehicle suppliers. Mark holds a Ph.D. in Materials Science from Northwestern University’s McCormick School of Engineering and a Master’s in Mechanical Engineering from SUNY Buffalo. His doctoral research used AI to design optical meta-materials, enhancing microscope resolution. He has received prestigious honors, including the Department of Defense NDSEG Fellowship, Northwestern’s Presidential Fellowship, and the Ryan Fellowship.
Organization:
CORE studio | Thornton Tomasetti
Presenter:
Sergey Pigach
Engineering Intelligence: Practical Applications of AI in Structural Engineering Practice
Presentation Abstract
Artificial Intelligence is no longer a distant future. It is actively shaping how structural engineers work, collaborate, and innovate. This session offers a practical look into how Thornton Tomasetti’s CORE studio is advancing AI integration within the firm, with a focus on real-world tools and workflows that enhance engineering practice. Attendees will explore the firm’s hands-on experimentation with generative models, domain-specific co-pilots, and applications of agentic workflows, as well as strategies for cross-disciplinary collaboration that ensure AI tools align with engineering priorities. The presentation will also share lessons learned in promoting firmwide adoption, cultivating technical fluency, and building an inclusive innovation culture that empowers all team members to contribute to AI-driven transformation.
Speaker Bio
Sergey Pigach is a Senior Associate Applications Engineer at CORE studio | Thornton Tomasetti. Sergey’s work builds on his architectural training by bridging the domains of technology and design, driving him to develop computational tools for architects, designers, and engineers. Since joining CORE studio he has worked on desktop and web-based projects including Swarm, a cloud compute solution for Grasshopper; ShapeDiver, a desktop client integration following a merger; and—most recently—Cortex, CORE Studio’s new MLOps platform.
Organization:
University of Southern California
Presenter:
David Gerber
Digital Twining a Living Lab
Presentation Abstract
The Living Lab Project is an innovative Viterbi initiative designed to enhance academic research and provide practical learning experiences through real-time monitoring and analysis of the new Ginsburg Hall building. Leveraging sensors embedded in the building’s systems and integrating cutting-edge digital twin technology, this project captures and analyzes data on energy usage, water consumption, building health and occupant well being, and more, offering a comprehensive dataset for faculty and student research. The project treats our newest building, a LEED platinum accredited building, as a scientific instrument to support both near term and longitudinal research across a multitude of disciplines including but not limited to Human Building Interaction, to AI, and sustainability related research fields
Speaker Bio
Dr. Gerber holds a joint appointment at USC’s Viterbi School of Engineering and the USC School of Architecture as a Professor of Civil and Environmental Engineering Practice and of Architecture. Dr. Gerber is the program Director for the Civil Engineering Building Science undergraduate program and the program Director for the Masters of Science in Emerging Technologies for Construction Program. Dr. Gerber is an associate director in the Office of Technology Innovation and Entrepreneurship. He teaches in the Viterbi School of Engineering, the School of Architecture and at the Viterbi Startup Garage. Dr. Gerber’s professional experience includes working in architectural, engineering and technology practices in the United States, Europe, India and Asia for Zaha Hadid Architects in London; for Gehry Technologies in Los Angeles; for Moshe Safdie Architects in Massachusetts; The Steinberg Group Architects in California; and for Arup as the Global Research Manager. Dr. Gerber’s research has been industry, fellowship, DoD, and NSF funded and is focussed on the development of innovative systems, tools, methods for design of the built environment. He has developed digital twin technologies and advises, and co advises PhD students from Architecture and Engineering on topics that integrate computer science, robotics, engineering, with architecture. David Gerber received his undergraduate architectural education at the University of California Berkeley (Bachelor of Arts in Architecture, 1996). He completed his first professional degree at the Design Research Laboratory of the Architectural Association in London (Master of Architecture, 2000), his post professional research degree (Master of Design Studies, 2003) and his Doctoral studies (Doctor of Design, June 2007) at the Harvard University Graduate School of Design. Dr. Gerber was the recipient of the Frederick Sheldon Fellowship at Harvard University and was a Research Fellow at MIT’s Media Lab in the Smart Cities group.
Organization:
Foster + Partners
Presenter:
Sherif Tarabishy
Design Complexity, Untangled
Presentation Abstract
At Foster + Partners, the Applied R+D team works at the frontier of design and technology. This talk explores how real-time simulation, distributed optimization, extended reality, and digital twins are reshaping the way we imagine and deliver projects. The session highlights a larger idea: the future of architecture will be defined by how we turn complexity into clarity, transforming information into insight and insight into better designs.
Speaker Bio
Sherif is an architectural engineer, software developer and researcher. He is an Associate Partner, Design Systems Analyst and leading the applied ML projects at Foster + Partners’ Applied R+D (ARD) group.
Sherif’s position there allows him to work on complex challenges on a daily basis, utilizing his expertise in geometry optimization, digital fabrication, virtual and augmented reality, and machine learning.
He is also a lecturer at The Bartlett in the MSc. in Architectural Computation and the MArch. in Architectural Design courses. For over 13 years, he has been lecturing, training and consulting at different universities and firms, with a focus on digital transformation in the AEC industry
Organization:
Walter P Moore & Associates
Severud Associates
Presenter:
GUSTAV FAGERSTRÖM, March, ARB, MSFE
STEVE REICHWEIN, PE, SE
A Parametric Structural Genome:
Using computational design to manage compound tolerances of multiple materials to create the world‘s largest double curved outdoor LED screen
Presentation Abstract
Las Vegas’ Sphere has the capacity to entertain a seated audience of up to 18,500. The interior features the largest, high-resolution LED screen in the world, paired with 164,000 speakers as well as 4D features, including scent and wind. The exterior, meanwhile, is wrapped in 580,000-sq.-ft of programmable lighting made up of approximately 1.2 million LED “pixels”. This presentation will focus on the spherical layering of the Sphere, making it possible to fit a high-fidelity display screen on top of a 500 ft diameter sphere in an extreme climate. Surrounding the performance venue itself is the geosphere exoskeleton that’s known as the “Exosphere”. Outboard of this primary structural steel, which is based on geodesic triangulation, is a layer of curved secondary structural steel known as “Trellis” which was preassembled into mega-panels on the ground and flown into place. On top of the Trellis sits the tertiary layer, which is the carrier of the LED pixels themselves. This layer, known as “Lattice” is made out of extruded aluminum, panelized off-site, and cold-warped in place to fit the Trellis panels’ curvatures prior to their installation.
Access to relevant data is essential for high quality, fact-based decision making. While engineers have always approached their work in this manner, the modern project workflow has brought about a specific, significant change. Client expectations have grown beyond the concept of a “final” deliverable to now include a continuous influx of data upon which they base key business decisions. Engineers are now purveyors of data just as much as they are consumers of it. On Sphere, the engineering team implemented parametric design early in the design process to help make informed decisions. Early conversations were held regarding fabrication and erection with W&W/AFCO Steel, contracted to deliver primary and secondary steel packages as well as with SACO Systems, the party responsible for the design and fabrication of the exterior LED solution. This open dialog early in the process enabled informed decisions through the incorporation of realistic fabrication and erection considerations and costs into the optimization functions. Through detailed estimates by W&W/AFCO together with casting manufacturer Cast Connex for a cast steel node option, a comparative analysis was developed which showed that casting the nodal connections of the Exosphere offered significant technical advantages over conventionally fabricated nodes.
By design, the goal at completion was for the Exosphere’s geometry to generally be within 2 in. of the target geometry and for out-of-tolerance between any two adjacent nodes to be less than L/500. From this – itself quite ambitious for a project of this size – superstructure tolerance target, the team needed to get down to glass curtain wall-like tolerances at the outermost layer supporting the LED:s. Extensive simulation showed that anything beyond +/- 10 mm out of position of any given LED pixel would distort the overall image. Added to this were also challenges from differential movements metals during the ~180°F temperature swings that are not uncommon in a desert climate. Making it all ultimately come together while staying within acceptable tolerances could only have been achieved using data-rich, high-fidelity parametric models of all the constituent systems, as well as robust protocols for data sharing and interpretation. Las Vegas Sphere was envisioned to awe the spectator and to elevate the entertainment experience to a new level and, thanks to the collaborative, computational design-aided process and creative thinking that was poured into its design and construction, it now stands as an architectural and structural landmark.
Speaker Bio
GUSTAV FAGERSTRÖM, March, ARB, MSFE
Gustav Fagerström is a Principal with Walter P Moore’s and a co-founder of the firm’s New York office. With dual master degrees from Sweden and the United Kingdom, he is a registered architect and the Digital Practice Leader with the Enclosure Engineering group.
STEVE REICHWEIN, PE, SE
Upon obtaining an integrated MAE/BAE degree in Architectural Engineering from the Pennsylvania State University, Steve joined Severud Associates as a structural engineer in 2009 and is currently a principal of the firm.
Steve has developed vast knowledge and experience in parametric design and modeling utilizing innovative techniques and geometric base three-dimensional parametric software, such as Rhinoceros 3D, Grasshopper, Revit, and Dynamo. Additionally, Steve has experience with integration between geometric based three-dimensional parametric software and finite element structural analysis software, such as SAP, ETABS, and RAM Structural System. Steve has applied this experience to many projects with structural complexity, such as Sphere, JFK Terminal 6, and TSX Broadway.
Steve is actively involved in professional organizations, where he currently serves on the board of directors as treasurer for SEAoNY and is a member of the ASCE 24 Committee on Flood Design. In addition to his active participation with professional organizations, Steve regularly volunteers to conduct lectures and webinars at various institutions, including his alma mater Penn State. He also volunteers for CANStruction and has run the NYC Marathon in support
of the NYRR Team for Kids charity.
Organization:
ARENA-AI
Presenter:
Pratap Ranade
Artificial Intuition: Building an AI Mind for Electromagnetic Design
Presentation Abstract
Most advances in computational design focus on mechanical structure — domains we can visualize and have evolved an intuition for. But as modern hardware becomes increasingly software defined, the unseen and unintuitive world of electromagnetism is taking center stage. Conventional solvers can simulate fields, yet they cannot imagine new ones. In this talk, I’ll share how we’re pushing past that frontier by creating artificial intuition — AI systems that learn physical behavior inductively, not deductively. Drawing inspiration from quantum experiments like the Kondo mirage, where discovery outpaced simulation, I’ll show how our team built Atlas: an AI that learns directly from electromagnetic test data to verify, optimize, and eventually postulate new designs. We’ll share results from realworld applications in semiconductors and aerospace, and offer a teaser of what’s to come over the next twelve months.
Speaker Bio
Pratap Ranade, ARENA-AI
The Unreasonable Effectiveness of Simulation Intelligence
Presentation Abstract
Scientific rigor & engineering reliability have always been important yet contentious topics in the AI field. Recent AI trends crank up model sizes, but at what costs? Transparency and verifiability, amongst others that are core to industrial R&D—not to mention the massive spending. These costs are perhaps felt the most in physics simulation and digital engineering. Enter simulation intelligence (SI). SI is not antithetical to AI, rather it is the pragmatic approach to bringing AI capabilities into industrial R&D. Rather than LLMs atop legacy engineering tools or Foundation Models to opaquely replace physics solvers, we look to the combinatorial possibilities available when SI motifs are brought together—namely differentiable physics programming and surrogate modeling, yielding multiphysics modules. This talk will describe the distinction, that is: static CAE simulations vs dynamic simulators, bespoke surrogate models vs flexible multiphysics modules, massive black-box AI vs efficient programmatic SI. Examples from the SI Platform will elucidate end-to-end digital engineering pipelines, in diverse sectors from nuclear energy and data centers, to aerospace and automotive safety.
Speaker Bio
Alexander Lavin is a leading expert in AI-for-science and probabilistic computing. He’s Founder & CEO of Pasteur Labs (and non-profit “sister” Institute for Simulation Intelligence), reshaping R&D with a new class of AI-native simulators, commercializing in energy security, aerospace, materials & manufacturing sectors (https://simulation.science). For the last dozen years, Lavin has focused on artificial general intelligence (AGI) research with top startups in neuroscience and robotics (Vicarious, Numenta), and sold his prior ML-simulation startup Latent Sciences to undisclosed pharmaco in neurodegeneration R&D. Lavin also serves as AI Advisor for NASA, overseeing physics-ML efforts for the NASA-ESA “Digital Twin Earth” projects. Previously, Lavin was a spacecraft engineer with NASA and Blue Origin, and won several international awards for work in rocket science and space robotics (including Google Lunar XPrize during graduate studies at Carnegie Mellon). Lavin was named Forbes 30 Under 30 in Science, and a Patrick J. McGovern Tech for Humanity Changemaker
From 3 Configurations to 300: Rapid Trades for Advanced Aircraft Design
Presentation Abstract
Aircraft development timelines have collapsed from 7 years to 18 months, but design tools still assume you have years to iterate. The result: teams freeze architecture in week 2, before they understand the design space, and spend the rest of the program managing the consequences.
The core problem is going from requirements-to-design is just too slow. Serial design evaluations, manual CAD updates that fail to parametrize correctly, and expensive simulation cycles create weeks-long iteration loops.
nTop solves this through three architectural principles: Parametric models that remain robust under any design change. No geometry failures, no manual repairs; integrated notebooks capturing engineering knowledge in executable form; and GPU-native solvers enabling interactive design-analysis cycles with performance feedback in minutes.
What’s the alternative? Exploring 3-4 hand-crafted configurations slowly or quickly committing to a single concept. Neither is likely to win. nTop enables systematic exploration of hundreds of variants in the time that traditional approaches evaluate three.
This presentation demonstrates real examples: Group 1-3 UAS configurations generated and flight-tested in weeks, hypersonic vehicle trade studies evaluating hundreds of variants, and rapid weapons platform sizing with integrated CFD.
The result: teams explore more, fail fast, and learn faster—improving win rates through comprehensive trade studies and defensible performance predictions.
Speaker Bio
Organization:
Neural Concept
Presenter:
Luca Zampieri
Empowering Organizations with Engineering Intelligence to Revolutionize Product Development
Presentation Abstract
In today’s highly competitive landscape, engineering organizations face increasing pressure to deliver complex, high-performing products at an accelerated pace, all while managing tighter margins. To maintain an edge, teams must shorten design cycles and enhance product performance and quality simultaneously.
However, traditional simulation and optimization tools often fall short of meeting the demands of today’s fast-moving production environments. Design teams struggle to fully utilize the insights from these tools and seamlessly integrate them into their workflows. Engineering Intelligence (EI) represents a significant advancement, leveraging modern AI techniques to overcome these challenges. EI enables a paradigm shift by offering multi-physics and multi-component generative design, more flexible automation, and the ability to harness historical data to expedite simulations.
Adopting EI offers a transformative approach, integrating simulation, CAD, and engineering data into an intelligent, cohesive platform that accelerates the product development lifecycle from concept to market. By drawing on enterprise engineering knowledge and existing processes, EI facilitates near-autonomous design, significantly reducing development time.
At the heart of this transformation is a new breed of engineers—the CAE Data-Scientists—who blend simulation expertise with data science skills. Empowered by the innovative NC platform, these engineers have a massive impact on their organizations by building and deploying EI workflows rapidly and broadly while remaining connected to existing tools and processes.
EI has already proven its value in real-world applications. An automotive supplier has seen higher RfQ win rates, faster development times, and significant cost savings. A major OEM in the energy sector rebuilt its design chain for a critical component, achieving 50% faster design cycles and improving annual throughput by thousands of megawatt-hours. This presentation will demonstrate how EI can tackle today’s most pressing engineering challenges and deliver measurable ROI within 18 months.
Speaker Bio
Luca Zampieri graduated from Ecole Polytechnique Fédérale de Lausanne (Switzerland) and Politecnico di Milano, with master’s degrees in Mathematical engineering and Computational engineering. After his graduation, he worked as a researcher in the Computer Vision Laboratory of EPFL from which Neural Concept would spin-off. He is a founding member of Neural Concept. He first focused on research then solution design. Luca is now Engineering Director US for the company.
Organization
Scawo3D
Presenter:
Philip Schneider + Timo Zollner
Computational Design for Assembly: Automating Design Workflows for 3D Concrete Printed Freeform Staircases
Presentation Abstract
Building large freeform reinforced concrete staircases has always been a challenge. Traditional methods rely on labor-intensive wooden or EPS formwork, making many designs too expensive. This can be changed with Selective Paste Intrusion, a new 3D concrete printing technique by Scawo3D using a large particle bed, with no constraints related to print overhangs or angles.
While fabrication now allows full geometric freedom, the design process became the bottleneck. Our previous AutoCAD-based solution, initially developed for producing G-codes for CNC-milling EPS formwork blocks, was not viable for 3D printing. Manual 3D modeling made scaling production impossible, leaving the printer underused. To solve this, Timo Harboe Zollner developed an automated workflow that cuts design time by up to 95%. This approach balances automation with intuitive user input, transforming 2D geometry into finely detailed 3D models in minutes. It integrates SubDs, meshes, volumetric modeling, and implicit modeling, achieving in moments what once took days.
This presentation highlights the adaptation of computational design to a new production method—one with only few geometric constraints yet capable of achieving material properties comparable to standard concrete.
Speaker Bio
Philip Schneider Computational & Architectural Design Lead at Scawo3D and founder of Skeno. He holds a M.A. from TU Munich with a focus on computational methods in architecture and specialises in 3D concrete printing by Selective Paste Intrusion at an architectural scale. Since 2022, he has led the design and fabrication of the first projects realised by SPI in academia and industry.
Timo Harboe Zollner is the founder of Timo Harboe ApS, a Copenhagen-based consultancy specializing in automating processes related to geometry, particularly within additive manufacturing. With a background in structural engineering and computational design, Timo collaborates with clients to develop parametric workflows and digital tools that streamline complex design and fabrication processes. His recent projects include automating the generation of 3D-printed formwork for freeform concrete staircases together with Scawo3D
Conformal Lattice Design Made Easy: A CAD-Integrated Approach
Presentation Abstract
TETMET has developed an innovative process to produce large-scale lattice structures in an automated way, enabling applications across multiple industries.
However, existing lattice design software has significant limitations, particularly when it comes to creating efficient, manufacturable conformal lattice structures. Most available tools were developed with general 3D printing in mind, offering only basic latticing capabilities that fail to meet the demands of more advanced applications.
Our approach takes a different path by integrating lattice design seamlessly into traditional CAD workflows. By combining the flexibility of CAD with the specific requirements of lattice generation, we significantly enhance the design process—allowing engineers to work with familiar tools while unlocking new possibilities for complex, high-performance structures.
Speaker Bio
Rachel holds a PhD in Lattice Structure Design and leads the Application Engineering team at TETMET. She specializes in transforming complex customer challenges into innovative, lightweight lattice solutions, bridging cutting-edge research with real-world applications.
Organization
Princeton University
Presenter:
Tuo Zhao
Super-Modular Chiral Origami Metamaterials
Presentation Abstract
Metamaterials with multimodal deformation mechanisms resemble machines, especially when endowed with autonomous functionality. A representative architected assembly, with tunable chirality, converts linear motion into rotation (1). These chiral metamaterials with a machine-like dual modality have potential use in areas such as wave manipulation, optical activity related to circular polarization and chiral active fluids. However, the dual motions are essentially coupled and cannot be independently controlled. Moreover, they are restricted to small deformation, that is, strain ≤2%, which limits their applications. Here we establish modular chiral metamaterials (2), consisting of auxetic planar tessellations and origami-inspired columnar arrays, with decoupled actuation. Under single-degree-of-freedom actuation, the assembly twists between 0° and 90°, contracts in-plane up to 25% and shrinks out-of-plane more than 50%. Using experiments and simulations, we show that the deformation of the assembly involves in-plane twist and contraction dominated by the rotating-square tessellations and out-of-plane shrinkage dominated by the tubular Kresling origami arrays. Moreover, we demonstrate two distinct actuation conditions: twist with free translation and linear displacement with free rotation. Our metamaterial is built on a highly modular assembly, which enables reprogrammable instability, local chirality control, tunable loading capacity and scalability. Our concept provides routes towards multimodal, multistable and reprogrammable machines, with applications in robotic transformers, thermoregulation, mechanical memories in hysteresis loops, non-commutative state transition and plug-and-play functional assemblies for energy absorption and information encryption.
References:
(1) Frenzel, T., Kadic, M. & Wegener, M. Three-dimensional mechanical metamaterials with a twist. Science 358, 1072–1074 (2017).
(2) Zhao, Tuo (presenter), Dang, X., Manos, K., Zang, S., Mandal, J., Chen, M., & Paulino, G. H. Modular chiral origami metamaterials. Nature, 640(8060), 931-940 (2025).
Speaker Bio
Tuo Zhao is a postdoctoral research associate at Princeton University. His expertise is in computational mechanics, nonlinear topology optimization, soft robotics, and mechanical metamaterials. Tuo is currently addressing the scalability challenge for developing useful metamaterials. By integrating an untethered actuation scheme (e.g., three-dimensional magnetic fields and micro-magnetic responsive materials), he designs micro-robotic machines with tunable properties on demand.
Organization:
STILFOLD
Presenter:
Julia Hannu
Greener by Every Fold. Strength in Every Curve.
Presentation Abstract
This talk introduces STILFOLD’s innovative origami-inspired manufacturing process, where metal sheets are folded into form. The process uses both straight and curved crease folding, expanding the possibilities of how sheets can be transformed into products. This, to make curved crease folding accessible to a wider community of designers and engineers – moving it from a niche research technique into a scalable industrial method. Our aim is to develop a more environmentally friendly way of making things – reducing the number of parts, energy consumption, material use and transportation needs. Achieving this involves multiple layers of complexity: from designing folding patterns of efficient structures to developing dedicated folding systems for production at scale.
The presentation will share insights into how STILFOLD is pushing to transform folding into a sustainable and practical approach to manufacturing – and what that could mean for the future of design, engineering, and production.
Speaker Bio
Julia Hannu is a Software Engineer and Computational Design Lead at STILFOLD, where she develops digital tools and algorithms to enable new approaches to sustainable manufacturing and design. Her work centers on transforming complex geometric challenges into practical, efficient, and user-friendly solutions. With a background in architecture and an MSc in Architectural Computation from UCL, she combines experience from practice and academia to bridge technology, design, and sustainability.
Organization:
MIT
Presenter:
Alfonso Parra Rubio
Crease, Fold, Transform.
Presentation Abstract
Folding is a fundamental process found throughout nature on multiple scales. Rather than altering the material itself, folding transforms its shape, offering a powerful means of engineering without compromising integrity.
This presentation explores, from an engineering and design perspective, the unique potential of folding and discrete assembly as a design and manufacturing tool across multiple scales in engineering.
From millimeter-scale bulk cellular materials to meter-scale structural corrugations and actuated robotic systems, and ultimately to architectural shell structures spanning tens of meters, folding enables the creation of high-performance, architected materials.
Speaker Bio
Alfonso Parra Rubio is a PhD candidate at the Massachusetts Institute of Technology, working at the Center for Bits and Atoms led by Neil Gershenfeld. His research explores how folding and discrete assembly can be combined to design and manufacture architected materials across multiple scales: from bulk cellular materials (millimeters to centimeters), to structural corrugations and actuated systems (centimeters to meters), and up to architectural-scale shell structures (meters to decameters). His work fundamentally explores how materials and structures are designed, engineered, manufactured, and assembled. In addition to his academic research, he founded RnKolektive, a collaborative platform for sculptural exploration. This parallel practice focuses on mixed-media works that merge folding techniques with blown glass, creating pieces that use the same research contributions but with an expressive intention.
CDFAM NYC 2025 Gallery
