Generative Manufacturing for Human-Centric Production Systems through GenAI and the Metaverse
Research Seminar Series
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Date
27 Apr 2026
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Organiser
Department of Industrial and Systems Engineering, PolyU
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Time
11:00 - 12:30
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Venue
Online via ZOOM
Speaker
Prof. Xingyu Li
Remarks
Meeting link will be sent to successful registrants. If you have enquiries regarding E-certificate after the seminar, please contact david.kuo@polyu.edu.hk.
Summary
This presentation will introduce generative manufacturing, a novel manufacturing paradigm that operationalizes generative artificial intelligence (GenAI) and the metaverse to enable natural, context-based interaction between humans and machines. Unlike conventional cyber–physical systems (CPS) that rely primarily on raw data exchange, generative manufacturing is grounded in interpretable and communicable contexts, such as natural language, visual cues, and immersive experiences. These contexts constitute abstract representations that integrate heterogeneous data, probabilistic beliefs, symbolic rules, knowledge bases, and human expertise. This presentation will illustrate the foundational mechanism by which manufacturing tasks are realized through context sharing among humans and generative agents within the metaverse, including: (i) avatar agents that encode human biometric, motion, and skill states; (ii) generative resource agents that fuse multimodal sensor data to cognize situations and feasible actions; and (iii) generative function agents that execute functions such as planning, prediction, and diagnosis on demand.
This presentation further highlights two emergent production-system behaviors enabled by generative manufacturing: (1) convergent intelligence for generating decisions by fusing human expertise, sensor data, and domain knowledge; and (2) multiverses that synthesize probabilistic what-if futures grounded on the sensor data. Together, these mechanisms enable the future production systems to transit beyond descriptive and predictive analytics, reflecting “what happens,” toward prescribing “what should be done.” This shift repositions humans from passive interpreters of sensor data to active refiners of prescriptive foresight and final decision-makers, thereby ensuring that humans remain central to manufacturing governance.
Keynote Speaker
Prof. Xingyu Li
Assistant Professor
School of Engineering Technology, Purdue University
Dr. Xingyu Li is currently an Assistant Professor in the School of Engineering Technology at Purdue University, West Lafayette. Before joining Purdue, he was an Adjunct Assistant Research Scientist at the Department of Mechanical Engineering at University of Michigan - Ann Arbor. Dr. Li received his Ph.D. degree in Mechanical Engineering from the University of Michigan – Ann Arbor in 2018. Dr. Li is currently a CIRP Research Affiliate, an ASTAR Visiting Fellow, an AnalytiXIN Fellow, and a corresponding expert in Engineering, he is also a recipient of Best Editorial Board Member of Engineering (2025), Best Student Research Presentation at NAMRC (2024), Best Paper Award at CIRPe (2024), Best Reviewer of OMEGA (2023), Outstanding Reviewer of Journal of Manufacturing Systems (2023), Best Paper Award at the 2019 IEEE AI4I, the Ford COVID-19 Innovation Challenge Award, and the Presidents Health and Safety Award. Dr. Li has authored over 50 publications in journals and conferences, including leading journals such as CIRP Annals - Manufacturing Technology, IISE Transactions, Scientific Reports, Journal of Manufacturing Systems, Robotics and Computer-Integrated Manufacturing, International Journal of Production Economics, International Journal of Production Research, Reliability Engineering and System Safety, European Journal of Operational Research. He has chaired or served as a member of editorial boards and scientific and organizing committees for international conferences, including DigiTwin 2024 for Manufacturing Sustainability, Safety, and Resilience), CIRP Annals (2026-Present), CIRP CMS (2024–2026), CIRPe (2023–2025) and IEEE ReMAR 2024. Dr. Li has also chaired sessions at prominent conferences such as CIRPe (2023–2025), NAMRC (2024), INFORMS (2023) and NSFC-RGC (2023), and served as track (co-)chair and symposium organizer at ASME MSEC 2026, ASME IMECE (2025–2026) and IEEE AI4I 2023.
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