Workshops

Time: 9:00am – 12:00pm

Presenters: Ali Hasanzadeh, Arizona State University and Dr. Farhad Ameri, Arizona State University

Description: Engineering systems increasingly rely on data-driven methods, yet lack shared semantics, which often limits interoperability, reuse, and reasoning across tools and domains. Applied Ontology offers a systematic approach to addressing these challenges by providing formally grounded representations of definitions and relations. This workshop introduces participants to semantic computing through the lens of Basic Formal Ontology (BFO) and Industrial Formal Ontology (IOF), widely adopted upper-level ontologies used across a variety of scientific and industrial knowledge systems.

The workshop will introduce core ontological concepts—such as objects, processes, functions, and relations—and knowledge patterns to demonstrate how a well-formed semantic framework supports consistent data integration, knowledge modeling, and automated reasoning, thereby enabling the creation of inferred knowledge. Through practical examples drawn from engineering and manufacturing contexts, participants will learn how BFO-based ontologies enable improved system interoperability, traceability, and model-driven decision support. No prior background in ontology is required. The workshop is intended for researchers and practitioners interested in leveraging semantic technologies to enhance engineering design, analysis, and lifecycle integration.

Time: 9:00am – 12:00pm

Presenters: Christopher McComb, Carnegie Mellon University and Jessica Menold, Penn State University

Description: This tutorial introduces an open-source software ecosystem for rigorous, reproducible research in engineering design. Participants will learn how the design-research library suite supports the full research workflow: defining benchmark problems, building and evaluating AI agents, structuring controlled experiments, and analyzing results. The tutorial is centered on a hands-on workflow that connects the major libraries in the ecosystem (i.e., problems, agents, experiments, and analysis) so attendees can see how methodological choices translate into executable research pipelines. The session is designed for researchers and practitioners interested in AI for engineering design, design automation, and computational design studies. By the end of the tutorial, participants will understand how to set up a reproducible design-research study, run a simple agent-based experiment, and interpret resulting data using a shared, extensible framework. The broader goal is to help the community move toward more transparent, comparable, and reusable computational design research.

Time: 9:00am – 12:00pm

Presenter: John Morris, University of Alabama in Huntsville Description: This workshop walks participants through practical methods for creating digital twins that can be immediately composed with other twins to form aggregate systems. Attendees will learn about constraint hypergraphs, a graphical method for capturing system behavior, before building a digital twin of a real-world asset. Throughout the workshop, participants will discover how to form function-based models of physical systems, integrate information flows from different digital engineering software tools such as CAD and PLM, and experience how constraint hypergraphs enable autonomous simulation and knowledge retrieval from the digital twin. Participants are expected to bring a device capable of writing and running Python scripts.

Time: 9:00am – 12:00pm

Presenter: Elisa Koolman, University of Texas at Austin

Description: As designers of the built environment, engineers' perspective on who designs are for can limit or broaden access to products and spaces. The power of social and environmental systems to remove access is one model of disability highlighted in Disability Studies. By understanding how designers can incorporate accessible design principles—informed by Disability Studies, Disability Justice, and Design Justice—we can continue to build a more accessible environment. In this workshop, we present the design community with a brief history of the intersection between disability and design, research on accessible design principles, and an opportunity to explore ways to integrate these principles in research and practice by:

• Engaging in group discussion on our context and experiences as designers
• Interacting with existing designs that integrate Accessible Design Principles to different extents
• Brainstorming integration strategies for participants' research and practice

By the end of this workshop, participants will have gained a deeper understanding of accessibility in design, how they and other researchers and practitioners can implement accessible design principles, and resources on accessible design principles to be passed along to students and peers.

Time: 9:00am – 1:00pm

Presenter: Alfonso Fuentes-Aznar, Rochester Institute of Technology

Description: Participants in this workshop will learn the principles of advanced gear design using IGD - Integrated Gear Design, the primary computational tool for the virtual generation and advanced simulation of gear drives. Through IGD, attendees will apply Tooth Contact Analysis (TCA) and Finite Element Analysis (FEA) to optimize the mechanical performance of different types of gear drives. The workshop covers among other topics, the application of micro-geometry modifications to gear tooth surfaces directed to eliminate edge contacts, as well as the evaluation of loaded transmission errors and mesh stiffness to reduce noise and vibration. Furthermore, the contents include the compensation of errors of alignment caused by shaft deflections and specialized design strategies for spiral bevel gears as well as planetary or pericyclic gear drives. The connection of IGD with the main commercial FEA computer programs will also be covered. By the end of this workshop, participants will be ready to use IGD to design gear systems that are quieter, stronger, and more reliable for power transmission.

Time: 1:00pm – 5:00pm

Presenter: Mahaveer Satra, MathWorks

Description: High-fidelity models, such as those based on FEA (Finite Element Analysis), CFD (Computational Fluid Dynamics), and CAE (Computer-Aided Engineering) models can take hours or even days to simulate. These full-order high-fidelity models, while being useful for detailed component design, are too slow and therefore impractical for system-level simulation, control design, and Hardware-in-the-Loop testing. For example, a finite element analysis model that is useful for detailed component design will be too slow to include in system-level simulations for verifying your control system or to perform system analyses that require many simulation runs. A high-fidelity model for analyzing NOx emissions will be too slow to run in real time in your embedded system. Does this mean you have to start from scratch to create faster approximations of your high-fidelity models? This is where reduced-order modeling (ROM) comes to the rescue. ROM is a set of computational techniques that helps you reuse your high-fidelity models to create faster-running, lower-fidelity approximations. In this workshop, you will learn how to create AI-based reduced order models using the Simulink add-on for Reduced Order Modeling to replace high-fidelity models.

Time: 2:00pm – 5:00pm

Presenters: Daniele Grandi, Autodesk; Kevin Acker, Autodesk; Tyson Fogel, Autodesk and Jiwon Jun, Autodesk

Description: Modern mechanical assemblies are becoming increasingly complex, requiring coordination across multiple disciplines. Yet today's CAD tools remain largely geometry-centric, limiting their ability to capture functional intent, structured requirements, and the reasoning behind design decisions. This gap makes multidisciplinary trade-offs difficult, keeps validation workflows fragmented, and leaves critical knowledge implicit rather than computable.

This interactive workshop explores emerging ideas from Autodesk Research at the intersection of AI and design, with a focus on functional and assembly design. Participants will explore what it would mean for design software to explicitly represent function, the limitations of multidisciplinary reasoning in current modeling paradigms, and how AI can offer richer representations of CAD assemblies. Through hands-on activities, attendees will experiment with leveraging LLMs to reason about assemblies, evaluate trade-offs, and support early-stage conceptual development.

The workshop aims to gather input on what next-generation CAD systems should represent beyond geometry, and how AI-driven workflows can better support functional reasoning, requirement validation, and multidisciplinary design exploration.

Time: 2:00pm – 5:00pm

Presenters: Dr. Carolyn Seepersad, Georgia Tech; Dr. Tucker Marion, Northeastern; Dr. Scott Ferguson, NC State

Description: The ASME Journal of Mechanical Design (JMD) New Author Development Workshop is designed to help emerging and returning scholars strengthen their ability to publish high-quality research in JMD. The workshop focuses on the full path from idea framing to final submission, with particular attention to positioning contributions, aligning manuscripts with the journal's standards, navigating double-blind review, and responding effectively to reviewer feedback. It is intended to lower barriers for newer authors, broaden participation in the journal's community, and improve the overall quality and readiness of submissions. More broadly, the workshop supports JMD's author development mission by pairing practical guidance with editorial insight to help researchers translate promising design scholarship into publishable work.

Time: 2:00pm – 5:00pm

Presenters: Ting Liao, Fatemeh Mozaffar, and Leah Chong

Description: Human-AI teaming in engineering design is advancing quickly, but the field still faces foundational questions about the role of automation, the balance between technical capability and human judgment, and the forms of collaboration that will matter most in practice. This workshop brings together researchers and practitioners to examine emerging directions in human-AI teaming through a more interactive format than a traditional speaker series. The workshop will combine short perspective-setting talks with structured activities designed to build connections, surface shared challenges, and provoke discussion around key open questions in the field. Participants will engage in a needs-and-resources icebreaker to identify opportunities for collaboration, a landscape-mapping activity to situate their work within the broader research space, and a debate-oriented session in which small groups develop and defend contrasting perspectives on important issues in AI for engineering design. The goal is to strengthen the human-AI teaming community while generating sharper collective insight into where the field is heading and what kinds of research, tools, and practices are needed next.

Time: 9:00am – 4:00pm

Presenters: Dr. Wei (Wayne) Chen, Texas A&M University, Dr. Namwoo Kang, KAIST and Dr. Dule Shu, Toyota Research Institute

Description: Following the strong engagement and interdisciplinary discussions at our 2025 workshop, we propose a 2026 workshop that further explores how data, machine learning, and generative AI are transforming engineering design. The workshop will bring together researchers and practitioners from academia and industry to discuss challenges and opportunities spanning design datasets, representation learning, generative synthesis, optimization, inverse design, AI-enabled CAD, material and physics-informed design, and industrial deployment. The format combines invited talks, software demonstrations, a panel discussion, and an interactive team activity so that participants can learn both foundational ideas and practical lessons from real applications. By emphasizing dialogue across methods, tools, and domains, the workshop aims to identify pressing research gaps, surface emerging best practices, and build a community around responsible, effective, and impactful data-driven design. Attendees will leave with a clearer view of current capabilities, limitations, and high-value opportunities for future collaboration.

Time: 9:00am – 5:00pm

Presenter: Daniel Hulse, NASA

Description: Capturing a complex system's resilience to hazards is inherently challenging because of the scale and coupling of interacting dynamic behaviors which can further evolve when a system enters off-nominal conditions. Thankfully, there is no need to start from scratch, and many of the common mistakes can be avoided with the application of good methodology. Building on years of design research in the simulation of hazardous modes in complex systems, the fmdtools Python library provides a flexible simulation architecture that can be applied to a wide variety use-cases. This tutorial will cover the use of fmdtools to (1) model a system and its off-nominal behavior(s) (2) simulate its resilience to hazardous scenarios and (3) statistically analyze its resilience to these scenarios. Some basic familiarity with Python will be assumed.