Xinyi Tu

Orcid: 0000-0001-8914-6986

Affiliations:
  • Aalto University, Department of Energy and Mechanical Engineering, Finland
  • University of Cambridge, Institute for Manufacturing, Cyber-Human Lab, UK (2024)
  • Technical University of Munich, Department of Informatics, Germany (2018-2021)


According to our database1, Xinyi Tu authored at least 10 papers between 2021 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Assessing the Readiness of Augmented Reality for Industrial Assembly: A Deployment Study Comparing Immersive and Non-Immersive Solutions.
IEEE Trans. Vis. Comput. Graph., May, 2026

2025
Are We Ready for the Metaverse? Implications, Legal Landscape, and Recommendations for Responsible Development.
Digit. Soc., April, 2025

Playbour Camps and Virtual Sweatshops.
Proceedings of the 28th International Academic Mindtrek, 2025

Are We Measuring What Matters? Reframing Evaluation of Extended Reality for Industry 5.0 Work Environments.
Proceedings of the IEEE International Symposium on Mixed and Augmented Reality, 2025

TwinFlow: Empowering industrial material flow with data-sovereignty through digital twins.
Proceedings of the 23rd IEEE International Conference on Industrial Informatics, 2025

Leveraging Personal Digital Twins to Evaluate and Mitigate Cybersickness Within the Industrial Metaverse.
Proceedings of the Extended Reality - International Conference, 2025

2023
Ontology-based knowledge representation of industrial production workflow.
Adv. Eng. Informatics, October, 2023

TwinXR: Method for using digital twin descriptions in industrial eXtended reality applications.
Frontiers Virtual Real., March, 2023

Towards enabling reliable immersive teleoperation through Digital Twin: A UAV command and control use case.
Proceedings of the IEEE Global Communications Conference, 2023

2021
Control Accuracy Measurement of a Mixed Reality Application for Digital Twin based Crane Operation.
Dataset, June, 2021


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