Jiayu Su

--- Navigating the multidimensional universe of systems biology ---

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Hello! I am a PhD student in Systems Biology at Columbia University working under the guidance of Raul Rabadan and David Knowles. I earned my Bachelor’s degrees in Biology and Mathematics from Peking University in 2020, where I worked with Cheng Li on statistical methods for analyzing single-cell transcriptomics and multi-omics data. I have also studied and interned at the University of Chicago (2018) and Harvard Medical School (2019), and briefly worked as a bioinformatics engineer at a precision medicine startup during the pandemic.

My research focuses on developing statistical and computational methods to better understand human diseases, especially cancer. Key areas of my work include:

  • Understanding how alternative splicing contributes to cancer development.
  • Investigating the tumor microenvironment using spatial omics.
  • Exploring the connections between aging and cancer.
Splicing in cancer
Splicing dysregulation is a hallmark of cancer, leading to oncogenic isoforms. Identifying these can open new therapeutic possibilities.
Tumor microenvironment
The interaction between cancer cells and surrounding tissue affects immune response and treatment. Spatial multi-omics helps unravel this complex ecosystem.
Aging
Aging involves molecular changes that can lead to cancer. Studying the link between splicing, aging, and cancer offers insights into prevention and treatment.

News

Nov 01, 2024 The sisPCA paper (Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis) was accepted at NeurIPS 2024!
Feb 04, 2024 New personal website is online!
Dec 18, 2023 My first major work in PhD, “Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data”, is published on Genome Biology!
Jul 31, 2023 My undergrad work on measuring single-cell aging with Shulin Mao is out on Genome Research!

Selected publications

  1. sispca.png
    Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis
    Jiayu Su, David A. Knowles, and Raul Rabadan
    In Advances in Neural Information Processing Systems, 2024
  2. smoother.png
    Smoother: a unified and modular framework for incorporating structural dependency in spatial omics data
    Jiayu Su, Jean-Baptiste Reynier, Xi Fu, and 8 more authors
    Genome Biology, 2023
  3. scale.png
    A transcriptome-based single-cell biological age model and resource for tissue-specific aging measures
    Shulin Mao*Jiayu Su*, Longteng Wang, and 3 more authors
    Genome Research, 2023
  4. Single-cell transcriptome profiling reveals neutrophil heterogeneity in homeostasis and infection
    Xuemei Xie*, Qiang Shi*, Peng Wu, and 14 more authors
    Nature Immunology, 2020