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.
