Our submission, Making Bodily Experience Visible in Creative Work, was accepted to the UIST 2026 Student Innovation Contest! Presenting a live demo at UIST in November.
pronouns: she/her
I’m an undergraduate at UW–Madison majoring in Data Science & Information Science, advised by Professor Yuhang Zhao, Professor Kris Sankaran, and Professor Yukang Yan at the University of Rochester. I aspire to be an HCI researcher who designs and builds for empowerment. I approach HCI through a critical and feminist lens, with the goal of supporting our capacity to think, create, and express while attending to diverse cognitive, sensory, tacit, and embodied ways of knowing. I’m also interested in how AI and increasing automation influence labor (especially around data) and knowledge practices. Recently, I’ve been exploring these questions primarily through human–AI interaction, physical computing and information visualization.
“Technology is not neutral. We’re inside of what we make, and it’s inside of us. We’re living in a world of connections — and it matters which ones get made and unmade.”
updates
recentLed a Feminism Reading Seminars discussion, hosted by Runhua, on women players reimagining gender representation in Chinese video games.
Helped demo A11yBits toolkit + A11yMaker AI by Kosa et al. in the AI-Assisted Vision Workshop on Intelligent Assistive Technologies for Blind and Low Vision Individuals. Details: UW–Madison Leads Collaborative Effort to Advance Artificial Intelligence for Low Vision.
research
all research →Do Better Embeddings Lead to Better Judgments? A User Study of PCA and UMAP for Single-Cell Data
IEEE VIS ’26 Poster
abstract
Dimensionality-reduction visualizations are essential to modern biology, but the same data can yield different embeddings depending on algorithm and hyperparameter choices. Whether these choices influence analyst conclusions, and whether more faithful embeddings yield better conclusions, is unknown. We ran an exploratory within-subject study with 12 participants comparing PCA, UMAP set to default hyperparameters, and a tuned version of UMAP across clustering and trajectory tasks grounded in single-cell analysis workflows. Both UMAP conditions produced higher accuracy and confidence than PCA and were strongly preferred, and completion time did not differ significantly. However, tuning did not improve accuracy over default UMAP and higher confidence did not correspond to higher accuracy. These findings suggest that computational embedding fidelity and perceptual usefulness are related but distinct.
More infos coming soon.
a little more
I’m Hakka, born and raised in Meizhou, China. I like writing historical
fantasy inspired by both history and records of anomalies, photography,
sewing
I’m a huge fan of traditional garments, especially Hanfu (汉服). I have been studying and promoting Hanfu since primary school and have organized multiple cultural events that were covered by local newspapers.
,
gardening
Before transferring to Madison I spent two years in Ningbo, China studying Environmental Science. I used to lead a farming group where we grew vegetables and flowers in the campus garden.
My family, especially my mom, were big fans of gardening — this is the olive my mom planted.
, visiting
historical sites
My most recent trip is to Machu Picchu, Peru!
, and singing ballads along the way.
Before transferring to UW–Madison, I spent two years in Ningbo, China studying Environmental Science When I first entered college, I genuinely thought knowing the names and histories of every species in the world (homo sapiens included!) was the coolest thing. My friends started a natural history blog (微信公众号: 自然青年) where we wrote about different species and the environment — they did most of the writing though 🌿 with research around planetary science. If you’re thinking about transferring internationally or switching majors (or both!), I’d love to chat about my experiences!