Artificial Intelligence (AI) is increasingly embedded in engineering design processes, including design problem formulation, design evaluation, and design synthesis, empowering designer creativity (Yang et al., 2022). As one example, large language models (LLMs) have been used to assist creativity evaluation and early-stage reasoning (Obieke et al., 2025; Zhang et al., 2025). However, the effectiveness of these technologies depends not only on the performance of the algorithms and models, but also on how humans and AI work together as cohesive design teams (Gyory et al., 2021; Song et al., 2022). A growing number of studies show that AI is becoming an active participant in design teams, when appropriately integrated, AI can improve design performance, coordination, and creativity (Gyory et al., 2021; Song et al., 2022). At the same time, studies have revealed important challenges, including misaligned communication between humans and AI, poorly designed interaction attributes, and issues of AI ethics and trust (Kirgil-Budakli et al., 2025; Song et al., 2024). These findings indicate the need to move beyond algorithm-centric perspectives and toward a systems-level understanding of human-AI teaming in engineering design.

Human-AI teaming in engineering design is about the design of technical, cognitive, and social interactions and systems that enable humans and AI to jointly address complex, uncertain, and creative design tasks. This Special Theme focuses on Human-AI teaming as a central challenge for the next generation of engineering design. We welcome contributions that move beyond viewing AI as just a tool or an independent decision-maker, instead treating humans and AI as collaborative partners that bring together human thinking, human-AI communication, and computational intelligence.

We invite high-quality original research contributions addressing theoretical, methodological, and practical aspects of human-AI teaming in engineering design, including but not limited to:

• Models and frameworks of human-AI teaming in design.
• Design of AI roles in engineering design processes.
• Cognitive workload and mental stress management through human-AI collaboration in design tasks.
• Human-AI teaming impacts on design creativity.
• Human-AI interactions and communications in design teams.
• Human-AI knowledge co-creation, retrieval, and management.
• Ethics and trust in human-AI teaming for design.
• Experimental studies of human-AI teaming in engineering design tasks.
• Agentic design assistants and multi-agent workflows.
• Evaluation and benchmarking of human-AI teaming

Timeline:

• Special Theme Open Date:1st September 2026
• Manuscript Submission Deadline:31st March 2027

Accepted papers will be published following a continuous publication model.

Guest Editors:

• Dr Ji Han, University of Exeter, UK, j.han2@exeter.ac.uk
• Dr Binyang Song, Nanyang Technological University, Singapore, binyang.song@ntu.edu.sg
• Dr Yong Zeng, Concordia University, Canada, yong.zeng@concordia.ca

References:

Gyory, J. T., Song, B., Cagan, J., & McComb, C. (2021). Communication in AI-assisted teams during an interdisciplinary drone design problem. Proceedings of the Design Society, 1, 651-660. https://doi.org/10.1017/pds.2021.65

Kirgil-Budakli, R., Zeng, Y., & Akgunduz, A. (2025). Dynamic workload reallocation for human–robot teams based on real-time stress analysis. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 39, e18, Article e18. https://doi.org/10.1017/S0890060425100073

Obieke, C. C., Bridgeman, J., & Han, J. (2025). A framework of AI collaboration in engineering design (AICED). Proceedings of the Design Society, 5, 91-100. https://doi.org/10.1017/pds.2025.10023

Song, B., Gyory, J. T., Zhang, G., Soria Zurita, N. F., Stump, G., Martin, J., Miller, S., Balon, C., Yukish, M., McComb, C., & Cagan, J. (2022). Decoding the agility of artificial intelligence-assisted human design teams. Design Studies, 79, 101094. https://doi.org/https://doi.org/10.1016/j.destud.2022.101094

Song, B., Zhu, Q., & Luo, J. (2024). Human-AI collaboration by design. Proceedings of the Design Society, 4, 2247-2256. https://doi.org/10.1017/pds.2024.227

Yang, J., Quan, H., & Zeng, Y. (2022). Knowledge: the good, the bad, and the ways for designer creativity. Journal of Engineering Design, 33(12), 945-968. https://doi.org/10.1080/09544828.2022.2161300

Zhang, J, Han, J, & Ahmed-Kristensen, S. (2025). Chain-of-Thought for Design Creativity Evaluation. Proceedings of the ASME 2025 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 3B: 51st Design Automation Conference (DAC). Anaheim, California, USA. August 17–20, 2025. V03BT03A043. ASME. https://doi.org/10.1115/DETC2025-167500