Connecting Industry & Government to Accelerate Innovation in Engineering and Manufacturing through Computational Design, AI & Machine Learning
CD/DC continues the CDFAM Computational Design Symposium program, bringing together the most innovative designers, engineers and architects working across computational design, artificial intelligence, and data-driven engineering.
The event is an in-person forum focused on practical methods, real-world applications, and cross-disciplinary exchange.
- LOCATION: Washington DC
- DATES: July 15-16, 2026
- Registration Now Open
Submissions are now open to present at CD/DC for industry, software developers and academia. Full details and requirements are available on the submission page .
Space is limited, and the program is already filling very quickly for this event.
In Washington, DC, the program will be extended to include additional presentations and roundtable discussions aligned with U.S. government initiatives.
These sessions are intended to create additional points of engagement between industry, academia, and public-sector stakeholders aligned with the core focus of the CDFAM program.
Participating Organizations
Purpose
CD/DC convenes the ecosystem shaping the future of how things are designed, engineered, and delivered at scale and speed.
- Government: Align policy, funding, and infrastructure with emerging design and manufacturing capabilities.
- Suppliers: Integrate at the design phase to enable fast, flexible fulfillment.
- Engineering Leaders: Build system-level solutions with simulation-integrated, AI-enhanced workflows.
- Software Developers: Scale impact by embedding tools at the point of design, not just execution.
Focus Areas
- System-Level Design Integration
From materials to architecture , enabling vertical interoperability across design, simulation, and production. - Generative + Simulation-Driven Engineering
Support decision-making across performance, cost, and manufacturability from the earliest phases of development. - Connected Digital Supply Chains
Feed validated, production-ready data to suppliers to reduce iteration cycles and accelerate delivery. - Agile Manufacturing Enablement
Leverage flexible manufacturing platforms through up-front computational workflows and standards-based data exchange. - Public-Private Infrastructure for Innovation
Establish common frameworks to support scalable, cross-sector collaboration between industry and government.
Who Should Join
- Engineering organizations deploying simulation-integrated workflows across product development.
- Software platforms enabling generative design, simulation, AI and machine learning augmented, and system modeling.
- Government agencies supporting industrial strategy, defense, energy, infrastructure, or sustainability.
- OEMs and suppliers building modular, responsive supply chains.
- National labs and research institutions focused on digital thread, design science, and model-based systems engineering.
Register to Attend
Standard Registration
$1250
Until July 15th
Early Bird Registration
$850
Until June 1st, or Sold Out
Academic Registration
$550
Until July 1st
PROGRAM
Currently Under Development & Subject to Change
Organization:
CDFAM
Presenter:
Duann Scott
Welcome to CD/DC
Presentation Abstract
Welcome to CDFAM Washington D.C. opening remarks giving context to the event and it’s program.
Speaker Bio
Duann Scott is the founder of the CDFAM – Computational Design Symposium, bringing together experts across design, engineering, and software development to explore the future of computational design at all scales.
He is also the Executive Director of the 3MF Consortium, driving the development of an open data standard for additive manufacturing.
With a background spanning industry, academia, and software, Duann focuses on advancing innovation in digital design and advanced manufacturing.
Organization:
NASA Goddard
Presenter:
Ryan McClelland
Text to Spaceship
Presentation Abstract
Speaker Bio
From a young age, Ryan McClelland has been captivated by futurism and technology, aspiring to contribute to a brighter future. As a Research Engineer in NASA GSFC’s Instrument Systems and Technology Division, he pursues developing and implementing digital engineering technologies for space-flight missions. Ryan is particularly excited about the potential of Artificial Intelligence, Virtual Reality, Generative Design, and Digital Manufacturing to accelerate space systems development.
Ryan’s work using AI to develop spaceflight structures has been featured by NBC News, The New York Times, Dezeen, Popular Science, and Aviation Week. He was recently named to the Fast Company 20 in AI list. In addition to his research, Ryan has played a significant role in various flight missions, including designs currently on orbit aboard the Hubble Space Telescope and International Space Station.
Organization:
Atomic Machines
Presenter:
Marta D’Elia
Minimizing the thought-to-thing time at Atomic Machines
Presentation Abstract
Atomic Machines is developing a completely new AI-native digital micro-manufacturing technology stack that will enable new classes of microdevices which we call MEMS 2.0. Critical to the mission is minimizing “thought-to-thing” time, i.e., the latency between an idea and a manufacturable device. Rather than maximize AI usage, we pursue a generate-to-solve strategy that uses as little AI as necessary, using AI to blend models grounded in physics, constraints, and verification to ensure our designs are trustworthy by construction.
In this talk we present an end-to-end workflow that converts an informal description into a precise set of engineering requirements. From this input, the system generates a multi-physics simulation of a first candidate device drawn from a catalog, and closes the loop modifying it with a manufacturability-first design optimization approach. We automatically move from informal descriptions to producing parts that meet performance targets while satisfying process constraints, tolerances, and assembly requirements.
We demonstrate our “Matter Design Engine” on a single mechanical component in an electromagnetic actuator, showing requirement formalization, simulation instantiation, and generation of manufacturable designs evaluated against acceptance tests.
Speaker Bio
Marta D’Elia is the Director of AI and Modeling & Simulation at Atomic Machines and an Adjunct Professor at Stanford University’s Institute for Computational and Mathematical Engineering. Her work focuses on scientific machine learning, physics-based simulation, and data-driven modeling for complex multiscale systems. She develops AI-enabled modeling approaches that integrate numerical simulation, machine learning, and uncertainty quantification to accelerate engineering design and manufacturing innovation. Prior to Atomic Machines, she held research and technical leadership roles at Meta, Pasteur Labs, and Sandia National Laboratories.
Organization:
Boston Dynamics
Presenter:
Brian Ringley
Authoring Autonomy
Presentation Abstract
Speaker Bio
Organization:
General Atomics Aeronautical Systems
Presenter:
Brandon DeMille
Computational Design in Aerostructures: Topology Optimization for Conceptual Design and Trade Studies
Presentation Abstract
Computational design methodologies, including topology optimization, are transforming airframe structures development by enabling rapid exploration of design configurations during early conceptual phases. This presentation demonstrates a workflow that enables informed decision-making across disciplines and accelerates the path from initial concept to detailed design. A fuselage case study illustrates the simultaneous optimization of composite laminates for skins, substructure geometry, and overall shaping. This integrated approach facilitates quantitative trade-offs among competing priorities such as cost, structural performance, manufacturability, and production rate.
Speaker Bio
Brandon DeMille has spent nearly two decades bridging the gap between computational design theory and real-world manufacturing constraints. As a Senior Staff Engineer in General Atomics Aeronautical Systems’ Advanced Manufacturing Technology group, he’s recognized as the go-to expert for topology optimization methods that help teams explore new concepts for aerostructures while keeping manufacturability front and center.
Before joining GA-ASI, Brandon led R&D teams at Callaway Golf, where his work on high-rate composite manufacturing processes and topology-optimized structures earned multiple industry awards and over 100 patents. Brandon brings deep technical expertise and hands-on experience taking concepts from optimization results to finished hardware. He holds degrees in Physics, Economics, and Mechanical Engineering from the University of California at Santa Barbara.
Organization:
Istari Digital
Presenter:
Rebeka Melber
The Digital Thread in the Real World: Multiple Partners, Multiple Tools, One Truth
Presentation Abstract
As the Department of Defense accelerates adoption of digital engineering and advanced manufacturing, the challenge is no longer defining the digital thread—it is executing it across a fragmented Defense Industrial Base (DIB). This session will explore a consortium-based approach to demonstrating an end-to-end digital thread spanning design, build, operations, and sustainment—executed within each partner’s native environment.
Rather than forcing tool or data standardization, this effort enables participating organizations to use their own systems, data architectures, and processes while securely sharing only what is necessary to maintain a federated, authoritative source of truth. The result is a practical model for interoperability that reflects real-world constraints: multiple vendors, distributed ownership, and varying levels of digital maturity.
Speaker Bio
Rebeka “Cam” Melber is the Director of Programs at Istari, where she oversees program execution and works closely with government and industry teams adopting next-generation engineering capabilities. Her career has focused on helping complex defense programs transition to modern digital infrastructure and accelerating the adoption of new technologies within sensitive mission environments. Drawing on experience across the Department of Defense, her work centers on making advanced engineering tools accessible to the people who need them most. Rebeka has led several first-of-their-kind capabilities and brings a blend of strategic vision, engineering discipline, and operational execution to advancing how complex systems are designed and delivered.
Organization:
nTop
Presenter:
Jan Vandenbrande
Fast and Robust Design with Implicit Functions and Direct Simulation
Presentation Abstract
Current Computer Aided Design systems excel in static detailed design but are too fragile and slow to support Design Exploration and Multidisciplinary Design Optimization for conceptual and preliminary design. This talk introduces a new approach to modeling products that overcomes these shortcomings based on implicit functions popularized in the animation industry. The main benefits of the approach is that is responsive to the need to design and redesign products in days or weeks and not month or years because of absolute robustness to parametric change minimizing human intervation; lightning fast evaluations leveraging GPUs; and performing analysis directly from the representation w/o the need of human intervention to generate cumbersome and error prone meshes.
Speaker Bio
Dr. Jan Vandenbrande is currently the VP for Aerospace and Defense for nTop and advisor to DARPA focusing on computational design and manufacturing. He previously served as Vice President of SRI International’s Future Concepts Division (formerly Xerox PARC), driving disruptive innovation in advanced production, clean technologies, and intelligent systems for societal and economic impact. Earlier, as a DARPA Program Manager in the Defense Sciences Office, he initiated and funded transformative research in design, manufacturing, materials, and mathematics to deliver breakthrough capabilities for future DoD platforms and the public good.
Before joining DARPA he was a Technical Fellow and Senior Manager of the Applied Math group at Boeing where directed the development of in house computational tools that enabled breakthrough design and manufacturing processes that improved Boeing’s products. He was the original author of GEODUCK, an advanced geometry and math system to enable Multi-disciplinary Design Optimization, a system still in use after 25 years.
At Unigraphics, now Siemens NX, Dr. Vandenbrande developed the initial architecture and user interface for the next generation Computer Aided Manufacturing (CAM) system and improved the system’s computational performance and accuracy. He is a former associate editor of JCISE, AIEDAM and CAD. He received his Ph.D. in Electrical Engineering from the University of Rochester and an engineering degree from the Vrije Universiteit van Brussel, Belgium. Jan is a frequent invited keynote speakers, published eight papers, presented at numerous conferences and holds five patents.
Organization:
Arena Physica
Presenter:
Pratap Ranade
Artificial Intuition: Building an AI Mind for Electromagnetic Design and Engineering
Presentation Abstract
Speaker Bio
Organization:
C-Infinity
Presenter:
Sai Nelaturi
AI Enabled Assembly Configuration Spaces
Presentation Abstract
Speaker Bio
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Organization:
Luminary
Presenter:
Dheeraj Vemula
Physics AI-Driven Optimization Across Multi-Domain Engineering Applications
Presentation Abstract
This presentation explores how Physics AI surrogate models, trained on vast GPU-accelerated datasets, shift the engineering loop from days to seconds. By enabling real-time 3D inference across UAVs, submarines, and supersonic missiles, these models accurately capture complex physics, such as precise pressure and shear stress fields, shock interactions, and boundary layer effects, directly from data.
By replacing expensive traditional meshing and solving with a near-instant inference loop, the talk will highlight key transformative engineering applications, including:
- Multi-objective Optimization: Rapidly evaluating complex design trade-offs, such as maximizing aerodynamic efficiency for Collaborative Combat Aircraft (CCA) and balancing submarine drag against internal volume constraints.
- Cross-Disciplinary Integration: Breaking engineering silos by unifying and accelerating the workflows between aerodynamics and structural analysis.
Ultimately, we will demonstrate how the real-time computation of thousands of design variations provides a scalable pathway to fundamentally compress development timelines for next-generation maritime and aerospace vehicles.
Speaker Bio
Dheeraj Vemula has 8 years of experience in the CAE simulation space. Dheeraj specializes in the of AI/ML-driven simulation and digital twins. His background spans product development and application engineering, underpinned by a Master’s in Mechanical Engineering from NCSU and a Bachelor’s from IIT Madras.
Organization:
InfinitForm
Presenter:
Dr. Michael Bogomolny
Requirements to Production Part in Minutes: How Physical AI Closes the Loop Between Optimization and Manufacturing
Presentation Abstract
The gap between optimized geometry and manufacturable components has been the defining constraint of computational design for three decades. Topology optimization produces brilliant forms that machinists cannot cut. Those forms are not editable in CAD / or CAD friendly. Simulation validates performance that mainstream manufacturing cannot reproduce. The result: design cycles measured in months, not days, and engineering organizations forced to choose between what is optimal and what is buildable.
InfinitForm was built to eliminate that tradeoff. The platform takes geometrical, engineering, manufacturing and cost constraints as input and outputs production-ready parametric CAD geometry, optimized simultaneously for structural performance and the specific manufacturing process it will be produced with, whether CNC machining, additive manufacturing, casting, extrusion, or injection molding. Every output carries full design history, constrained sketches, and parametric relationships, making it immediately editable in the CAD environment the engineering team already uses. GPU-accelerated solvers and optimizer, the system compresses what previously required weeks of iteration into minutes of compute.
This talk presents the technical architecture behind that capability, the manufacturing constraint modeling approach that makes outputs buildable rather than merely optimal, and results from production deployments at aerospace, defense, and advanced manufacturing organizations. It examines what changes when design for performance and design for manufacturing are solved as a single problem rather than sequential steps, and what that means for the engineering organizations, defense programs, and industrial supply chains now entering the Physical AI era.
Speaker Bio
Dr. Michael Bogomolny is an industry leader in AI-driven design optimization and advanced manufacturing with over two decades of experience in the engineering software field. As the Founder and CEO of Infinitform, Michael is driving innovation in design processes by seamlessly integrating manufacturing and performance criteria at the earliest stages, delivering faster, more efficient, and production-ready designs.
Prior to founding Infinitform, Michael co-founded ParaMatters, a leading generative design software platform for additive manufacturing, later acquired by Carbon. He also served in senior engineering roles at Hyperloop and Altair Engineering, where he developed cutting-edge solutions in structural optimization.
Recognized globally for his expertise in structural and multidisciplinary optimization, computational geometry, and CAD/CAE, Dr. Bogomolny has authored more than 25 scientific peer-review publications. He holds a Ph.D. from Technion – Israel Institute of Technology and completed postdoctoral research with the prestigious TopOpt group at the Technical University of Denmark.
Organization:
Not a Robot Engineering
Presenter:
Matthew Shomper
From Horns to Armor: Biomimicry, Computational Design, and the Future of Impact Protection
Presentation Abstract
Nature 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.
Speaker Bio
Matthew is a visionary leader in the computational design of advanced 3D-printed medical implants, with 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:
Pasteur Labs
Presenter:
Alexander Lavin
Pasteur Labs
Presentation Abstract
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.
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
Register Interest
Register your interest to participate in, attend, or sponsor the upcoming CD/DC event taking place in Washington, DC in July 15-16 2026. Submit your details below and we will follow up with updates and opportunities as the program develops.
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