28 citations · 53 across the 10 of their papers we have counts for
10 papers
VisGuardian: A Lightweight Group-based Privacy Control Technique For Front Camera Data From AR Glasses in Home Environments
Shuning Zhang, Qucheng Zang, Yongquan `Owen' Hu +7
Always-on sensing of AI applications on AR glasses makes traditional permission techniques ill-suited for context-dependent visual data, especially within home environments. The ho…
Position: Human-Robot Interaction in Embodied Intelligence Demands a Shift From Static Privacy Controls to Dynamic Learning
Shuning Zhang, Hong Jia, Simin Li +4
The reasoning capabilities of embodied agents introduce a critical, under-explored inferential privacy challenge, where the risk of an agent generate sensitive conclusions from amb…
From Patient Burdens to User Agency: Designing for Real-Time Protection Support in Online Health Consultations
Shuning Zhang, Ying Ma, Yongquan `Owen' Hu +4
Online medical consultation platforms, while convenient, are undermined by significant privacy risks that erode user trust. We first conducted in-depth semi-structured interviews w…
Actual Achieved Gain and Optimal Perceived Gain: Modeling Human Take-over Decisions Towards Automated Vehicles' Suggestions
Shuning Zhang, Xin Yi, Shixuan Li +7
Driver decision quality in take-overs is critical for effective human-Autonomous Driving System (ADS) collaboration. However, current research lacks detailed analysis of its variat…
Vision-Based Multimodal Interfaces: A Survey and Taxonomy for Enhanced Context-Aware System Design
Yongquan 'Owen' Hu, Jingyu Tang, Xinya Gong +6
The recent surge in artificial intelligence, particularly in multimodal processing technology, has advanced human-computer interaction, by altering how intelligent systems perceive…
Exploring Device-Oriented Video Encryption for Hierarchical Privacy Protection in AR Content Sharing
Yongquan Hu, Dongsheng Zheng, Kexin Nie +3
Content sharing across multiple Augmented Reality (AR) displays is becoming commonplace, enhancing team communication and collaboration through devices like smartphones and AR glas…
Adanonymizer: Interactively Navigating and Balancing the Duality of Privacy and Output Performance in Human-LLM Interaction
Shuning Zhang, Xin Yi, Haobin Xing +3
Current Large Language Models (LLMs) cannot support users to precisely balance privacy protection and output performance during individual consultations. We introduce Adanonymizer,…
Towards Enhanced Context Awareness with Vision-based Multimodal Interfaces
Yongquan Hu, Wen Hu, Aaron Quigley
Vision-based Interfaces (VIs) are pivotal in advancing Human-Computer Interaction (HCI), particularly in enhancing context awareness. However, there are significant opportunities f…
Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health
Yongquan Hu, Shuning Zhang, Ting Dang +4
Integrating physiological signals such as electroencephalogram (EEG), with other data such as interview audio, may offer valuable multimodal insights into psychological states or n…
MultiSurf-GPT: Facilitating Context-Aware Reasoning with Large-Scale Language Models for Multimodal Surface Sensing
Yongquan Hu, Black Sun, Pengcheng An +3
Surface sensing is widely employed in health diagnostics, manufacturing and safety monitoring. Advances in mobile sensing affords this potential for context awareness in mobile com…