Yujie Tao is a Computer Science Ph.D. candidate and Knight-Hennessy Scholar at Stanford University. She is part of SHAPE Lab, advised by Prof. Sean Follmer and also works closely with Prof. Jeremy Bailenson in Virtual Human Interaction Lab. She obtained MS from University of Chicago, advised by Prof. Pedro Lopes, and BA from UNC-Chapel Hill with a double major in Media & Journalism and Computer Science. Her research asks how future computing can deepen user awareness of real-world, physical interactions rather than pulling users into virtuality. She develops systems that computationally surface naturally occurring yet overlooked sensory information (e.g., manual interaction sounds, muscle engagement) to support wellbeing (e.g., mindfulness) and performance (e.g., motor control). Yujie publishes in leading Human-Computer Interaction venues, including ACM CHI, UIST, IMWUT, and TOCHI, receiving one Best Paper Award, two Best Demo Awards, and one Honorable Mention Award. Her work has been covered by media outlets such as Digital Trends, New Atlas, and The Washington Post.
Yujie Tao, Jordan Egelman, Jeremy N. Bailenson
ISMAR 2024 Paper
Yiran Zhao*, Yujie Tao*, Grace Lee, Rui Maki, Alexander Adams, Pedro Lopes, Tanzeem Choudhury
IMWUT 2023 Paper
Conny Lu, Praneeth Chakravarthula, Yujie Tao, Steven Chen, Henry Fuchs
ISMAR 2020 Paper