Kaylee Yaxuan Li
Ph.D. Candidate
Computer Science and Engineering
University of Michigan
I am a Ph.D. candidate in Computer Science and Engineering at the University of Michigan, advised by Alanson P. Sample and Kang G. Shin.
My research develops wearable and ubiquitous AI systems that interpret human activity and context from multimodal data. I focus on sensing and efficient semantic representations of daily life, long-horizon memory architectures for scalable reasoning, and proactive assistance on resource-constrained wearable and mobile platforms. My work seeks to transform everyday human experience into persistent, actionable intelligence that augments human perception, memory, reasoning, and decision-making, with broader implications for physical AI and human–agent interaction.
Selected Publications
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ECG Signal Construction From Heart Sounds via Single Node, Surface Acoustic Sensing
2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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Towards Context-aware Automatic Haptic Effect Generation for Home Theatre Environments
27th ACM Symposium on Virtual Reality Software and Technology (VRST 2021)
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Safe Navigation of Quadrotors with Jerk Limited Trajectory
Frontiers of Information Technology & Electronic Engineering, vol. 20, no. 1
