Ka I Chan she/her/hers

I am a first-year Ph.D. student at University of Michigan School of Information, advised by Professors Sun Young Park and Mark W. Newman. Before Michigan, I earned a master's degree in Data Science and Information Technology and a bachelor's degree in Psychology from Tsinghua University, where I was advised by Professors Yuanchun Shi and Yuntao Wang.

My research interests lie at the intersection of Human-Computer Interaction, Health Informatics, and Human-Centered AI. I take a human-centered approach to understand how patients and underserved populations navigate high-stakes life contexts, and design AI-powered systems to empower and support them towards better health and well-being.

Ka I Chan
Recent News
Mar 2026"Capturing Chewing and Swallowing with Earables: A Multimodal Dataset Across Contexts" accepted at CHI '26 Workshop.
Nov 2025"Human and Algorithmic Visual Attention in Driving Tasks" accepted at npj Artificial Intelligence, from my internship at Tsinghua AIR.
Sep 2025"A Review of Behavioral Closed-Loop Paradigm from Sensing to Intervention for Ingestion Health" accepted at IMWUT '25.
Aug 2025Started my Ph.D. at UMSI with a first-semester fellowship!

Selected Publications

* denotes equal contribution
Full list on Google Scholar →
IMWUT 2025
A Review of Behavioral Closed-Loop Paradigm from Sensing to Intervention for Ingestion Health
Jun Fang*, Yanuo Zhou*, Ka I Chan, Jiajin Li, Zeyi Sun, Zhengnan Li, Zicong Fu, Hongjing Piao, Haodong Xu, Yuntao Wang, Yuanchun Shi
A systematic review of 136 studies proposing a behavioral closed-loop paradigm that integrates sensing, reasoning, and intervention for adaptive ingestion health systems.
PDF DOI
CHI 2025
The Odyssey Journey: Top-Tier Medical Resource Seeking for Specialized Disorder in China
Ka I Chan, Siying Hu, Yuntao Wang, Xuhai Xu, Zhicong Lu, Yuanchun Shi
A qualitative study using Actor-Network Theory to reveal how hemifacial spasm patients in China navigate social networks and technology to overcome information asymmetries and access top-tier medical resources.
PDF DOI
UIC 2024
Automated Grading Hemifacial Spasm Using Smartphone Cameras
Ka I Chan, Bo Hei, Linghao Meng, Ruen Liu, Yuntao Wang, Chang Chen, Qingpei Hao, Yuanchun Shi
A smartphone-based AI system that detects and grades hemifacial spasm severity through facial keypoint analysis, achieving 88% detection accuracy aligned with clinical grading standards.
PDF DOI
International Journal of Human-Computer Studies
Beyond digital privacy: Uncovering deeper attitudes toward privacy in cameras among older adults
Weiwei Zhang, Jianing Yin, Ka I Chan, Tongxin Sun, Tongtong Jin, Jihong Jeung, Jiangtao Gong
A mixed-methods study revealing that older adults' privacy concerns with fall detection cameras extend beyond data protection to encompass dignity and perceived control over their aging identity.
PDF DOI