The ICAI 2026 Program Committee is inviting proposals for special sessions to be held during the conference (http://www.icai.org.cn/2026/Special%20Session.php), taking place on November 25-28, 2026, in Ningbo, China.
Each special session proposal should be well motivated and should consist of 8 to 12 papers. Each paper must have the title, authors with e-mails/web sites, and as detailed an abstract as possible. The special session organizer(s) contact information should also be included. All special session organizers must obtain firm commitments from their special session presenters and authors to submit papers in a timely fashion (if the special session is accepted) and, particularly, present them at the ICAI 2026. Each special session organizer will be session chair for their own special sessions at ICAI 2026 accordingly. All planned papers for special sessions will undergo the same review process as the ones in regular sessions. All accepted papers for special sessions will also be published by Springer's Lecture Notes in Computer Sciences (LNCS)/ Lecture Notes in Artificial Intelligence (LNAI)/ Lecture Notes in Bioinformatics (LNBI).
All the authors for each special session must follow the guidelines in CALL FOR PAPERS to prepare your submitted papers.
Proposals for special sessions should be submitted in ELECTRONIC FORMAT by http://www.icai.org.cn/icg/index.php at Special Session.

orders	Title	Organizers	Nationality
Special Session 1	Trustworthy AI for Advanced Manufacturing	Jeonghwan Gwak	Republic of Korea

1. Trustworthy AI for Advanced Manufacturing
Organizer:
Jeonghwan Gwak
Korea National University of Transportation
Email: jgwak@ut.ac.kr

Scope and Topics:
This special session focuses on trustworthy artificial intelligence for advanced manufacturing, with an emphasis on multimodal foundation models, digital twins, and edge intelligence. It aims to bring together researchers and industrial practitioners working on methods that address limited annotations, heterogeneous sensor data, changing operating conditions, and computational constraints in manufacturing environments. Topics of interest include multimodal representation learning, industrial visual inspection, anomaly detection, root cause analysis, prognostics and health management, physics-informed digital twins, sensor fusion, and efficient deployment on edge devices. The session also welcomes agentic AI approaches that combine manufacturing knowledge, diagnostic tools, and human-approved decision support. Submissions are encouraged to examine generalization across machines, production lines, or operating conditions and to report relevant measures of reliability, uncertainty, latency, and computational cost. Methodological contributions, reproducible benchmarks, and industrial case studies are welcome. The session seeks to advance AI methods whose practical value is demonstrated through clearly defined manufacturing problems and rigorous evaluation.