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I'm a

Hi, I am Siyu, currently a postdoctoral fellow in the Department of Biomedical Data Science at Stanford University, where I am advised by Dr. James Zou and Dr. Stephen Quake.


My research interests lie at the intersection of statistical machine learning, computational biology, stem cell engineering, and disease modeling. My mission is to leverage AI methodologies in biomedicine to accelerate our understanding of diseases.


I earned my PhD in Biomedical Engineering from Columbia University, where I am co-advised by Dr. Kam Leong and Dr. Elham Azizi. I hold a Bachelor's degree in Physics from Xi'an Jiaotong Unversity in China.

Project Lead

Projects Collaborated

Students mentored

Paper published

  • Postdoc, Biomedical Data Science, Stanford University, 2023 -
  • PhD, Biomedical Engineering, Columbia University, 2018 - 2023
  • BS, Physics with honors, Xian Jiaotong University, 2013 - 2017

    • Research

    My research spans multiple cutting-edge areas in biomedical data science.

    The application includes: cancer biology, vascular development and disorders, engineered tissues for disease modeling and drug testing.

    Below are the major research direactions I focus on:

    Generative AI in genomics

    I am interested in generative models such as probabilistic graphical models, and diffusion models that generate reliable genetic data through precisely designing cell state parameters. These models disentangle tissue complexity or complement missing or expensive data.

    Multimodal biomedical AI

    I am intested in mutimodal modal for general biomedical data, including genomics, imaging, clinical records to provide a more comprehensive understanding of biological processes and diseases. Specifically, I am working on spatial multi-omics integration for comprehensive understanding in tumor microenvironments

    Foundation model for biology

    My work also includes developing foundation models for human biomedical data, espeically on genomics data.

    Selected News

    Selected publications

    • All
    • Cancer biology
    • Generative AI in biomedicine
    • ML for tissue engineering
    • Multimodal biomedical AI
    • Biophysics
  • He, S.*, Zhu, Y.*, Tavakol, D.*, Ye, H., Lao, Y., Zhu, Z., Xu, C., Chauhan, S., Garty, G., Tomer, R., Vunjak-Novakovic, G., Zou, J., Azizi, E., Leong, K. Squidiff: Predicting cellular development and responses to perturbations using a diffusion model. bioRxiv (2024). [CODE] [Paper]



  • Xu, C.*, He, S.*, Zhu, Y., Crasto, G., Chen, C., Clay, M., Lao, Y., Leong, K. Vascular Organoid Generation from Human-Induced Pluripotent Stem Cells. JoVE (2024). In press.


  • He, S. Encoding spatial tumour dynamics with Starfysh. Nature Reviews Cancer (2024). [Paper]


  • He, S.*, Jin, Y.*, Nazaret, A.* et al. Starfysh integrates spatial transcriptomic and histologic data to reveal heterogeneous tumor–immune hubs. Nat Biotechnol (2024). [CODE] [Paper]



    • To see all publications >> click here

    Contact

    Siyu He

    Postdoc fellow,

    Department of Biomedical Data Science

    School of Medicine, Stanford

    siyuhe@stanford.edu