The 5th International Workshop on eXtended Reality for Industrial and Occupational Supports (XRIOS)

@IEEE VR 2026

8:30 AM - 12:30 PM (Sunday), March 22nd, 2026

(Timezone: Korea Standard Time, UTC/GMT +9 hours)

Overview

The eXtended Reality (XR) technologies have been applied to a wide range of industries and occupational areas for maintenance, quality control, training, education, remote collaboration, etc. The industries can benefit from XR by providing their employees with timely and efficient instructions. The users can improve their work performance while reducing mental and physical workload through effective XR systems. However, as workplace conditions become diverse, the XR technologies should be adaptive and innovative to meet the new industrial needs. Furthermore, as XR applications supporting industrial and occupational tasks include physical movements and activities, it is necessary to perform a variety of assessments from ergonomics and physiological perspectives.

This workshop—eXtended Reality for Industrial and Occupational Supports (XRIOS)—aims to identify the current state of XR research and the gaps in the scope of human factors and ergonomics, mainly related to the industrial and occupational tasks, and discuss potential future research directions. XRIOS will build a community that bridges XR developers, human factors, and ergonomics researchers interested in industrial and occupational applications.

Keynote Speakers

Manufacturing Physical AI: Enabling Autonomous Factories Through Virtual–Real Connected Intelligence

Abstract:

Physical AI refers to artificial intelligence systems capable of understanding physical interactions, spatial–temporal context, and the dynamics of real-world environments. Among its many potential domains, manufacturing is one of the most promising and impactful application areas.

At KAIST, we are leading a national initiative in Korea to develop autonomous factory AI that coordinates large-scale fleets of heterogeneous robots and automation systems using the principles of Physical AI. The core idea is to train AI in a high-fidelity virtual factory (digital twin), adapt and fine-tune the intelligence for a target manufacturing environment, and then seamlessly transfer this trained intelligence to real factory control systems. This virtual–real connected approach enables safe learning, rapid deployment, and significant improvements in operational performance.

In this keynote, I will introduce the concept of Physical AI for manufacturing, discuss the underlying virtual–real integration technologies, and present real industrial cases where this framework has been successfully applied in Korean factories. I will also outline future directions for XR-enabled digital twins and human–robot–environment interaction in autonomous manufacturing environments.

Bio:

Young Jae Jang received his Ph.D. in Mechanical Engineering from the Massachusetts Institute of Technology (MIT) in 2007, and dual M.S. degrees in Mechanical Engineering and Operations Research from MIT in 2001. He earned his B.S. in Aerospace Engineering from Boston University in 1997. He is currently a Professor in the Department of Industrial and Systems Engineering at the Korea Advanced Institute of Science and Technology (KAIST) and the Founding Director of the Center for KAIST Manufacturing Physical AI, where he leads research on next-generation autonomous manufacturing systems. Since 2025, Prof. Jang has served as the Principal Investigator of a USD 500 million national project on Manufacturing Physical AI, a flagship Korean government initiative aimed at realizing fully autonomous factories through AI-driven robot orchestration and digital twin technologies.

Young Jae Jang
(Professor of Industrial and Systems Engineering at KAIST, South Korea)

Immersion, Interaction, and Intelligence for Industrial Insight

Abstract:

A wide range of problems in a variety of industries require humans to make complex judgments about spatial objects, spatial environments, or even abstract information. In this talk, I will argue that with appropriate design, XR technologies are ideally suited to support such judgments. First, XR provides immersion, which helps users make sense of space Second, XR can make use of natural interaction, which helps users perform spatial tasks and make use of spatial memory. Finally, XR can be designed to provide intelligence, allowing AI features to support human users. I will illustrate these points with examples from our projects in diverse domains such as scientific visualization, defect inspection in additive manufacturing, and sensemaking in intelligence analysis. I will conclude by suggesting a research agenda for future industrial XR systems.

Bio:

Doug A. Bowman is the Frank J. Maher Professor of Computer Science at Virginia Tech. He is the principal investigator of the 3D Interaction Group, focusing on the topics of three-dimensional user interfaces, VR/AR user experience, and the benefits of immersion in virtual environments. Dr. Bowman is one of the co-authors of 3D User Interfaces: Theory and Practice. He has served in many roles for the IEEE Virtual Reality Conference, including program chair, general chair, and steering committee chair. He also co-founded the IEEE Symposium on 3D User Interfaces (now part of IEEE VR). He received a CAREER award from the National Science Foundation for his work on 3D Interaction, and has been named an ACM Distinguished Scientist. He received the Technical Achievement award from the IEEE Visualization and Graphics Technical Committee in 2014 and the Career Impact Award from IEEE ISMAR in 2021. His undergraduate degree in mathematics and computer science is from Emory University, and he received his M.S. and Ph.D. in computer science from the Georgia Institute of Technology.

Doug Bowman
(Professor of Computer Science at Virginia Tech)

Organizers

Hyungil Kim (hyungil@uic.edu) | University of Illinois Chicago, USA (Primary Organizer)
Isaac Cho (isaac.cho@usu.edu) | Utah State University, USA
Myounghoon Jeon (myounghoonjeon@vt.edu) | Virginia Tech, USA
Heejin Jeong (heejin.jeong@asu.edu) | Arizona State University, USA
Kangsoo Kim (kangsoo.kim@ucalgary.ca) | University of Calgary, Canada
Dongyun Han (dongyuh@clemson.edu) | Clemson University, USA
Ahmad Albawaneh (aalba@uic.edu) | University of Illinois Chicago, USA
Muskan Sarvesh (muskan.sarvesh1@ucalgary.ca) | University of Calgary, Canada
Bhairavi Jangle (bjangale@asu.edu) | Arizona State University, USA
Masiath Mubassira (masiath@vt.edu) | Virginia Tech, USA

International Program Committee

Bernardo Marques (bernardo.marques@ua.pt) | University of Aveiro, Portugal
Samuel Silva (sss@ua.pt) University of Aveiro, Portugal
Carlos Ferreira (carlosf@ua.pt) | University of Aveiro, Portugal
Paulo Dias (paulo.dias@ua.pt) | University of Aveiro, Portugal
Beatriz Sousa Santos (bss@ua.pt) | University of Aveiro, Portugal

Contact

For any questions related to the workshop or submission process, please contact us via email at xrios.workshop@gmail.com.

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