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A cross-layer system for multi-user volumetric video streaming over mmWave using 6DoF motion prediction and multi-lobe multicast to reduce redundancy.

Recommended citation: Zhang, D., Puqi Zhou, Han, B., and Pathak, P. (2022). "M5: Facilitating Multi-user Volumetric Content Delivery with Multi-lobe Multicast over mmWave." In Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys ’22), 31–46. ACM. Acceptance rate: 28%.
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Volumivive: An Authoring System for Adding Interactivity to Volumetric Video

Published in IEEE VRW 2023, 2023

An authoring system that adds interactivity to pre-recorded volumetric video for AR and VR through four interaction methods.

Recommended citation: Jin, Q., Liu, Y., Puqi Zhou, Han, B., Yarosh, S., and Qian, F. (2023). "Volumivive: An Authoring System for Adding Interactivity to Volumetric Video." In 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), 569–570. IEEE.
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Collaborative Online Learning with VR Video: Roles of Collaborative Tools and Shared Video Control

Published in CHI 2023, 2023

A within-subject study (N=54) comparing synchronized and non-synchronized video control in collaborative VR video viewing for online learning.

Recommended citation: Jin, Q., Liu, Y., Sun, R., Chen, C., Puqi Zhou, Han, B., Qian, F., and Yarosh, S. (2023). "Collaborative Online Learning with VR Video: Roles of Collaborative Tools and Shared Video Control." In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI ’23), 1–18. ACM. Acceptance rate: 24%.
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Theia: Gaze-driven and Perception-aware Volumetric Content Delivery for Mixed Reality Headsets

Published in MobiSys 2024, 2024

A gaze-driven, perception-aware volumetric content delivery system for mobile mixed reality headsets that reduces bandwidth while improving visual quality.

Recommended citation: Wu, N., Liu, K., Cheng, R., Han, B., and Puqi Zhou. (2024). "Theia: Gaze-driven and Perception-aware Volumetric Content Delivery for Mixed Reality Headsets." In Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services (MobiSys ’24), 70–84. ACM. Acceptance rate: 21%.
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MuV2: Scaling up Multi-user Mobile Volumetric Video Streaming via Content Hybridization and Sharing

Published in MobiCom 2024, 2024

An edge-assisted multi-user mobile volumetric video streaming system that hybridizes direct 3D streaming with remote rendering and shares transcoded views across users.

Recommended citation: Liu, Y., Puqi Zhou, Zhang, Z., Zhang, A., Han, B., Li, Z., and Qian, F. (2024). "MuV2: Scaling up Multi-user Mobile Volumetric Video Streaming via Content Hybridization and Sharing." In Proceedings of the 30th Annual International Conference on Mobile Computing and Networking (MobiCom ’24), 327–341. ACM. Acceptance rate: 19.09%.
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Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals

Published in CHI 2026, 2026

A testbed and MRVS system for multi-robot ground video sensemaking with public safety professionals, including a dataset of 20 patrol videos and 38 events of interest.

Recommended citation: Zhou, P., Asgarov, A., Hussain, A., Park, W., Paudyal, A., Shrestha, S., Tang, C., Lighthiser, M., Hieb, M., Xiao, X., Thomas, C., and Hong, S. (2026). "Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals." In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26). ACM. Acceptance rate: 25.3%.
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Attune: A Self-Annotation Tool for Understanding Robot Operator Attention Profiles

Published in UIST 2026, 2026

A pre-deployment elicitation tool that uses operator eye gaze to identify attention shifts, provide AI-assisted annotation, and characterize individual attention profiles for multi-robot supervision.

Recommended citation: Zhou, P., Hong, S. R., and Porfirio, D. (2026). "Attune: A Self-Annotation Tool for Understanding Robot Operator Attention Profiles." In The 39th Annual ACM Symposium on User Interface Software and Technology (UIST ’26). ACM.
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teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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Puqi Zhou

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🎉 Our paper, Attune: A Self-Annotation Tool for Understanding Robot Operator Attention Profiles, is accepted in UIST 2026

🎉 Our paper, Designing Multi-Robot Ground Video Sensemaking with Public Safety Professionals, is accepted in CHI 2026 in Barcelona, Spain.

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