Kuan Pang

Hi, I'm Kuan. 👋

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I am a Computer Science Ph.D. student at Stanford, advised by Prof. Jure Leskovec.

I work on building the AI Virtual Cell. I am particularly excited about (1) developing machine learning models that reason about biological systems across physical scales, (2) guiding frontier data collection with these foundation models, and (3) using these models to generate novel biological hypotheses.

Previously, I did my B.S. in {Computer Science, Bioinformatics and Computational Biology, and Statistics} @ University of Toronto and had the fortune to work at Vector Institute with Prof. Bo Wang.

selected publications

2026

  1. lumi-lab.gif
    LUMI-lab: a foundation model-driven autonomous platform enabling discovery of new ionizable lipid designs for mRNA delivery
    Haotian Cui**, Yue Xu**, Kuan Pang*, Gen Li*, Fanglin Gong*, Bo Wang†, and Bowen Li†
    Cell, 2026
    PDF

2025

  1. pulsar.gif
    PULSAR: a Foundation Model for Multi-scale and Multicellular Biology
    Kuan Pang*, Yanay Rosen*, Kasia Kedzierska, Ziyuan He, Abhe Rajagopal, Claire E Gustafson, Grace Huynh, and Jure Leskovec†
    bioRxiv, 2025
    PDF

2024

  1. bleep.gif
    Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning
    Ronald Xie, Kuan Pang, Sai Chung, Catia Perciani, Sonya MacParland, Bo Wang†, and Gary Bader†
    Advances in Neural Information Processing Systems, 2024
    PDF
  2. scgpt.gif
    scGPT: toward building a foundation model for single-cell multi-omics using generative AI
    Haotian Cui*, Chloe Wang*, Hassaan Maan, Kuan Pang, Fengning Luo, Nan Duan, and Bo Wang
    Nature Methods, 2024
    PDF

2023

  1. maester.gif
    MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition
    Ronald Xie*, Kuan Pang*, Gary D Bader†, and Bo Wang†
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
    ✨Selected as Highlight(top2.5%)✨
    PDF