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Erzhen Hu


I am a second-year Ph.D. student (Aug. 2021-present) at the CS Department at the University of Virginia, where I work on Human-Computer Interaction. My PhD advisor is Seongkook Heo.

My journey from sociology and psychology to HCI has taught me the value of socio-spatial theories and methods to motivate design. My current research focuses on developing new systems for distributed/hybrid meetings.

I'm interested in Human-Computer Interaction, Video-Mediated Communication, AR/VR for Remote Collaboration and Assistive Technologies.

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ThingShare: Ad-Hoc Digital Copies of Physical Objects for Sharing Things in Video Meetings

Erzhen Hu, Jens Emil Grønbæk, Wen Ying, Ruofei Du, and Seongkook Heo
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI), 2023

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OpenMic: Utilizing Proxemic Metaphors for Conversational Floor Transitions in Multiparty Video Meetings

Erzhen Hu, Jens Emil Grønbæk, Austin Houck, and Seongkook Heo
Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (CHI), 2023

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FluidMeet: Enabling Frictionless Transitions Between In-Group, Between-Group, and Private Conversations During Virtual Breakout Meetings

Erzhen Hu, Md Aashikur Rahman Azim, Seongkook Heo
Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI), 2022
doi / pdf / 30s preview / video figure / 8-min talk / 40-min talk /

Conceptualizing proxemic and F-Formation theories, FluidMeet is a video-conferencing system that enables out-group members to overhear group conversations while allowing conversation groups to control their shared level of context. Users within conversation groups can also quickly switch between in-group and private conversations.

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Enjoy the Ride Consciously with CAWA: Context-Aware Advisory Warnings for Automated Driving

Erfan Pakdamanian, Erzhen Hu, Shili Sheng, Sarit Kraus, Seongkook Heo, Lu Feng
Proceedings of the 14th International Conference on Automotive User Interfaces and Interactive Vehicular Applications (AutomotiveUI '22), 2022
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This work proposed context-aware advisory warning method (CAWA) for automated driving that detects the NDRT in which the driver is engaged and selects the type of modality based on the detected activity.

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Enabling Remote Hand Guidance in Video Calls Using Directional Force Illusion.

Archana Narayanan, Erzhen Hu, Seongkook Heo
In Companion Publication of the 2022 Conference on Computer Supported Cooperative Work and Social Computing (CSCW'22 Adjunct), 2022
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The remote meeting system enables guiding the remote partner’s hand with a handheld device creating directional force illusion using asymmetric vibration.

Design and source code from Jon Barron's website