Important Dates
- Submissions deadline: 30 November 2025
- Publication: May 2026 (ETA)
Intelligent Computer-Aided Design (CAD) is rapidly reshaping design, engineering, and manufacturing. By integrating artificial intelligence (AI), machine learning (ML), and advanced computational techniques, CAD systems are evolving beyond traditional geometric modeling tools into intelligent collaborators. These systems can now understand design intent, generate novel solutions, perform complex analyses, and optimize outcomes for multifaceted objectives.
This shift promises to revolutionize how products are conceived, developed, and delivered by enabling new levels of creativity, efficiency, customization, and performance. At the same time, CAD presents a rich and challenging testbed for AI, with its structured data, strict constraints, and inherent complexity.
This special issue of IEEE Computer Graphics and Applications (CG&A) aims to showcase the latest research and forward-looking developments in the field of Intelligent CAD. We welcome high-quality, original submissions that explore innovative theories, methodologies, applications, and systems at the intersection of AI and CAD. We especially encourage papers that demonstrate how intelligent systems can augment human creativity and transform real-world design workflows.
Types of Contributions:
- Research papers introducing novel models, methods, or systemsC
- Application papers highlighting impactful real-world deployment
- Position papers presenting visionary ideas, emerging challenges, or bold perspectives on the future of Intelligent CAD
Topics of Interest include (but are not limited to):
- Deep learning for CAD modeling and reverse engineering
- Reinforcement learning for design automation and optimization
- Predictive modeling and simulation using AI
- Topology optimization enhanced by AI
- Semantic enrichment of CAD models using AI techniques
- Knowledge capture and reuse through AI-driven methods
- AI-based mining of CAD repositories for pattern and insight discovery
- Generative design for additive manufacturing
- AI-driven design for manufacturing, assembly, and sustainability
- Personalized and adaptive CAD environments enabled by AI
- AI-enhanced user interfaces and design interaction
- Human-in-the-loop and co-creative CAD systems
- AI-supported collaborative and cloud-based CAD across roles and platforms
- Intelligent CAD applications in electronics, architecture, geospatial systems, healthcare, animation, and gaming
- AI-enabled design for emerging manufacturing paradigms such as 3D
Submission Guidelines:
For author information and guidelines on submission criteria, visit the Author’s Resources Page page. Please submit papers through the IEEE Author Portal and be sure to select the special issue or special section name. Manuscripts should not be published or currently submitted for publication elsewhere. Please submit only full papers intended for review, not abstracts, to the IEEE Author Portal. If requested, abstracts should be sent by email to the guest editors directly. Guest editors encourage early submissions to ensure faster processing.
In addition to submitting your paper to [Conference Name], you are also encouraged to upload the data related to your paper to IEEE DataPort. IEEE DataPort is IEEE’s data platform that supports the storage and publishing of datasets while also providing access to thousands of research datasets. Uploading your dataset to IEEE DataPort will strengthen your paper and will support research reproducibility. Your paper and the dataset can be linked, providing a good opportunity for you to increase the number of citations you receive. Data can be uploaded to IEEE DataPort prior to submitting your paper or concurrent with the paper submission.
Questions?
Contact the guest editors at:
- Yang Liu, CGA AE, Principal Researcher, Microsoft Research Asia
- Dave Kasik, CGA Department Editor, ACM Fellow, Senior Technical Fellow of Boeing
- Changjian Li, Assistant Professor, University of Edinburgh
- Hao Pan, Assistant Professor, Tsinghua University
