About

Human-centric manufacturing envisions a reciprocal partnership between people and machines. However, realizing this potential poses significant challenges in the development of advanced technologies. Specifically, differences between human and machine intelligence underscores the need to better understand AI’s role in facilitating workplace interaction. 

To highlight, addressing these challenges requires understanding how the development of AI-related skillsets can accommodate diverse cognitive and sensory-physical abilities across the workforce; how AI systems can interpret user intentions while managing procedural uncertainties during collaborative tasks; and the extent to which humans and machines can co-develop, engage in bi-directional learning, and achieve mutually beneficial goals.

Subsequently, through diverse perspectives, this one-day workshop aims to seek understanding of how co-development can drive innovation and generate shared values within evolving manufacturing ecosystems. Specifically, to gather insights into existing and emerging trends, review and correlate research and development works, and formulate actionable items as tangible research directions.

As such, we welcome contributions across multiple areas, including advancements in AI/machine learning models, aspects of human-machine collaboration (including robotics), knowledge transfer, learning and task planning, privacy and security, explainable and responsible AI, and use cases pertaining to human-centric manufacturing.

Topics of interest 

Related to human-centric manufacturing, topics include, but are not limited to the following:

• Situation aware and assistance systems

• Detection, tracking and monitoring 

• Planning for human uncertainty and error   

• Enhancing and amplifying human capabilities 

• Human-robot collaboration

• Human-in-loop agentic AI

• Digital twins and simulation

• Model interpretability and bias 

• Explainable AI

• Evaluation measures and empirical benchmarks

• Concepts and frameworks 

• Privacy protection and ethical issues

• Knowledge transfer across domains

• Industrial use cases 

Workshop format

The workshop will include morning and afternoon invited talks (details to be included shortly). Accepted papers will be structured as oral presentations, which we are looking to separate by related themes. To conclude the workshop, a panel discussion will aim to summaries key insight, while facilitating further discussion and knowledge sharing. 

Submission requirements 

We invite full technical papers (6 to 8 pages), and short/work-in-progress papers (2 to 4 pages), excluding references and supplementary material.  Accepted papers and the workshop schedule will be posted on this website. 

Papers submissions are required to be anonymized for single blind review. Please follow the AAAI formatting guidelines: https://aaai.org/conference/aaai/aaai-26/submission-instructions/ 

Paper submissions should be sent to: https://openreview.net/group?id=AAAI.org/2026/Workshop/HCM

Attendance 

Across different backgrounds, we welcome contributions from educators, researchers, and practitioners to promote discussions and collaboration in the development of human-centric solutions for manufacturing. 

Please note, for each accepted submission, at least one author must be physically present at the workshop. Details of the room venue will be provided nearer the time.

Timetable

• Workshop paper submissions due: Friday, October 24, 2025 

• Notifications sent to authors:  Friday, November 7, 2025

• Camera-ready paper deadline: Friday, November 28, 2025

• Workshop date: Monday, January 26 or Tuesday, January 27, 2026 (TBC)

Workshop chairs 

Mark Rice, Institute for Infocomm Research, A*STAR, Singapore  

Shijian Lu, Nanyang Technological University, Singapore  

Gu Ying, Institute for Infocomm Research, A*STAR, Singapore  

Lai Xing Ng, Institute for Infocomm Research, A*STAR, Singapore 

Enquiries on the workshop should be sent to: mdrice@i2r.a-star.edu.sg

Banner image by: chensiyuan, CC BY-SA 3.0, https://creativecommons.org/licenses/by-sa/3.0, via Wikimedia Commons