Greetings! 👋

I'm Peiyu Zhang

HCI Researcher and Software Engineer at UVA

I am a Systems and Information Engineering PhD candidate at the University of Virginia, advised by Prof. Sara Riggs. I am passionate about designing interfaces and systems that empower users to better harness emerging technologies such as AI and mixed reality. My research interests include human factors, multi-display interfaces in mixed reality, human-AI collaboration, and tangible interaction.

I am actively looking for software engineer or research intern for Summer 2026. Resume🔗

Publications

Web Pages as 3D Proxies in VR: A Design Framing and Preliminary Exploration

CHI 2026 Extended Abstract

DOI🔗 PDF🔗

Tianjie Shu*, Peiyu Zhang*
Novel VR web browsing experience with tabs represented by 3D proxies of real-world objects, supporting spatial and physical interaction.

Multitasking Across Physical and Virtual Displays: The Effect of Spatial Discontinuity and Task Load

🏆 IEEE VR 2026/Special Issue of TVCG (Best Paper Honorbale Mention Award)

DOI🔗 PDF🔗 Video🔗

Peiyu Zhang, Mohamad El Iskandarani, Sara Riggs
User study examining how the use of AR, spatial discontinuity between displays, and task load affect multitasking performance and perceived workload.

The Effect of Layout on Visual Search in Augmented Reality Multi-Window Displays

IEEE Transactions on Visualization and Computer Graphics (TVCG)

DOI🔗 PDF🔗

Peiyu Zhang, Mohamad El Iskandarani, Sara Riggs
User study examining how the spatial placement of multi-display AR, in relation to depth separation, information density, and the curvature of virtual multi-window displays, affects visual search performance.

The Effect of AI Assistance Timing on Performance and User Perceptions in Pathological Slide Diagnosis

Elsevier Applied Ergonomics

DOI🔗 PDF🔗

Peiyu Zhang, Zichen Ye, Ronggan Wei, Haiyan Niu, Hongxia Li, Mingjuan Wang, Peng Xue, and Sara Lu Riggs,
User study evaluating how the timing of AI-provided information affects clinicians' performance, workload, and trust and percieved usability of the AI tool.

Deep learning-assisted system improves practical effect in cervical cytopathology diagnosis: A comparative study of reading modes

Elsevier Modern Pathology

DOI🔗

Zichen Ye, Peiyu Zhang, Ronggan Wei, Haiyan Niu, Hongxia Li, Mingjuan Wang, Sara Lu Riggs, and Peng Xue
User study evaluating how the timing of AI-provided information affects clinicians' performance and workload when diagnosing cervical cytology slides.

Multitasking Between Realities: An Examination of Multitasking Using Augmented Reality Under Different Task Demand Levels

HFES Annual Meeting (ASPIRE) 2025

DOI🔗 PDF🔗

Peiyu Zhang and Sara Riggs
User study investigating how augmented reality through OST-HMDs impacts multitasking performance and perceived workload across different levels of task demand.

MoiréTag: A Low-Cost Tag for High-Precision Tangible Interactions without Active Components

🏆 ACM ISS 2024 (Honorbale Mention Award)

DOI🔗 PDF🔗

Peiyu Zhang, Wen Ying, Sara Riggs, and Seongkook Heo
A computer-vision based touch force sensing method that supports the creation of tangible interfaces.

Chinese colposcopists' attitudes toward the colposcopic artificial intelligence auxiliary diagnostic system (CAIADS): A nation-wide, multi-center survey

Sage Digital Health

DOI🔗 PDF🔗

Huike Wang*, Zichen Ye*, Peiyu Zhang*, Xiaoli Cui, Mingyang Chen, Aiyuan Wu, Sara Lu Riggs, Peng Xue, and Youlin Qiao
A nation-wide questionnaire that collected clinicians' sociodemographic information and assess their awareness, attitudes, and acceptance toward AI-assisted diagnostic system.

Fringer: A finger-worn passive device enabling computer vision based force sensing using moiré fringes

UIST 2022 Poster

DOI🔗 PDF🔗

Peiyu Zhang, Wen Ying, and Seongkook Heo
A finger sleeve that physically visualizes the force to allow a camera to estimate the force without using any active sensors.