Yiqun T. Chen

Stanford Data Science + DBDS; Statistical Rigor for Data Science.

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I am Yiqun Chen (pronunciation here), currently a Data Science Postdoctoral Fellow at Stanford University, working with Professor James Zou on applying advanced AI techniques to biomedical data. Previously, I completed my PhD in Biostatistics under the guidance of Professor Daniela Witten at the University of Washington, where I developed methods to test data-driven hypotheses. My application interest spans different fields of data science: from dermatology, social networks and epidemiology, as well as HCI and microbiome science.

Before graduate school, I earned undergraduate degrees in Statistics, Computer Science, and Chemical Biology with high distinction from the University of California, Berkeley. I’ve also gained industry experience in data science with Amazon Search and Waymo LLC.

I am always excited to explore collaboration opportunities, participate in reviews, and deliver talks. Please feel free to reach out to me via email at yiqun.t.chen[at]gmail[dot]com or schedule a meeting with me.

recent news

  • Excited to travel to MLCB 2023 to present our work GenePT and to moderate the industry discussion panel!
  • TWIGMA, our work (preprint) looking at AI-generative art, has been accepted to NeurIPS 2023.
  • I proposed a test for a difference in means for a single feature after clustering (preprint and software).

ūüéČ celebrate every (small) win

I have been fortunate to have received several awards and honors, including the Cornell Young Researchers Workshop in 2023, the Rising Stars in Data Science in 2022, the Best Paper Honorable Mention at CHI 2023, the Thomas R. Fleming Excellence in Biostatistics Award, the Student Research Paper Award at NESS 2022, the Best Award at WNAR 2021, the Young Investigator Award at CROI 2020, and the Outstanding Teaching Assistant Award from the School of Public Health at the University of Washington.

selected publications

  1. chi_paper_snippet.png
    Why, when, and from whom: considerations for collecting and reporting race and ethnicity data in HCI
    Yiqun Chen, Angela DR Smith, Katharina Reinecke, and 1 more author
    In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023
  2. genept_sticker.png
    GenePT: A Simple But Hard-to-beat Foundation Model For Genes and Cells Built From ChatGPT
    Yiqun Chen, and James Zou
    biorxiv.org/content/10.1101/2023.10.16.562533v1, 2023
  3. kmeans_inf.png
    Selective inference for k-means clustering
    Yiqun Chen, and Daniela M Witten
    Journal of Machine Learning Research, 2023