Engineering design is undergoing a profound transformation with the rise of generative artificial intelligence (AI)Generative AI focuses on creating new samples resembling its training data, using methods such as variational autoencoders, generative adversarial networks, diffusion models, and large language models. Generative Artificial Intelligence in Design (GAIDe) unlocks the ability to produce novel design alternatives across high-dimensional, multimodal spaces, accelerating innovation and expanding the scope of exploration for diverse objectives. GAIDe is enabling new ways of ideating, exploring, and optimizing designs across a wide array of domains. From conceptual ideation to manufacturability, from materials to sustainable systems, GAIDe represents a new frontier for how we approach complexity, creativity, and trade-off management in engineering design. At the same time, GAIDe introduces unique challenges compared to other fields, for example, limited and noisy design and engineering data, the need to respect physical or mechanical constraints, and domain-specific design principles and considerations.
This special issue invites contributions to explore, define, test, and expand the role of generative AI across all areas of engineering design by tackling the unique challenges in the domain of GAIDe. Topics of interest include, but are not limited to:
- Generative design methods for conceptual design and early-stage ideation
- Social and ethical implications of generative AI use in engineering design
- Applications of generative AI in systems design
- Integration of generative AI with materials design
- Human-AI co-design, creativity support, and interaction frameworks
- Design optimization by integrating generative AI
- Physics-informed or constraint-aware generative AI in engineering design
- Benchmarking GAIDe against conventional or hybrid engineering design methods
- Novel datasets designed to support applications of AI in design
- Use of multi-modal datasets (text, image, simulation, user data) in the design process
As a focus area within this broader paradigm, we highlight Generative Artificial Intelligence in Design for X (GAIDe for X): the use of generative AI to tackle design priorities such as sustainability, repurposability, manufacturability, inclusivity, ethics, and design justice. To that end, we also encourage submissions that address topics of GAIDe for X including but not limited to:
- Generative design for circularity, lifecycle assessment, and environmental sustainability
- Ethical frameworks and inclusive design enabled by generative AI
- Considerations of manufacturability or assembly when using generative AI for product development
- GAIDe for reliability, such as uncertainty management
- Case studies focused on the intersection of generative design and social impact
- Trade-off management across conflicting design goals using generative AI
The goal of this special issue is to gather an interdisciplinary community of researchers and practitioners across design, engineering, AI, manufacturing, sustainability, human-computer interaction, and more. We believe this issue will serve as a catalyst for future research, capturing the growing momentum around GAIDe and establishing a foundation for its role in shaping and guiding the future of engineering design.
Special Issue Timeline:
Paper Submission Deadline: February 15, 2026
Initial Reviews Completed: April 2026
Publication: October 2026 (in print); immediate on-line publication upon acceptance
Guest Editors
Xingang Li, University of Melbourne, Australia, xingang.li@unimelb.edu.au
Madhurima Das, University of Melbourne, Australia, madhurrima.das@unimelb.edu.au
Katja Holtta-Otto, University of Melbourne, Australia, katja.holttaotto@unimelb.edu.au
Zhenghui Sha, University of Texas at Austin, USA, zsha@austin.utexas.edu
Christopher McComb, Carnegie Mellon University, USA, ccm@cmu.edu
Liwei Wang, Carnegie Mellon University, USA, liweiw@andrew.cmu.edu
Ferdous Alam, Massachusetts Institute of Technology, USA, mfalam@mit.edu