Yubin Xie, PhD
I’m a Staff AI Scientist at Noetik. I develop machine learning models for spatial biology and oncology, including virtual cell models that use sequencing and imaging data to study cells in their tissue context.
I completed my PhD in the Tri-Institutional Program in Computational Biology and Medicine, working with Dana Pe’er at Memorial Sloan Kettering Cancer Center. My doctoral research focused on cancer progression and metastasis using single-cell and spatial data.
Selected publications
Full list on Google Scholar- Transcriptomic Plasticity Is a Hallmark of Metastatic Pancreatic Cancer
- The neuroendocrine transition in prostate cancer is dynamic and dependent on ASCL1
- MITI minimum information guidelines for highly multiplexed tissue images
- Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer
- The human tumor atlas network: charting tumor transitions across space and time at single-cell resolution
- Regenerative lineages and immune-mediated pruning in lung cancer metastasis
Presentations & community
- Co-organized ICBINB: Where Large Language Models Need to Improve at ICLR.
- Presented a SITC poster on virtual cell models and fibroblast–macrophage crosstalk in the lung cancer microenvironment.
- Presented OCTO-virtual cell at AACR, on modeling cell and tissue spatial biology for patient stratification and target discovery.
- Co-organized ICBINB: Challenges in Applied Deep Learning at ICLR.
- Co-organized ICBINB: Failure Modes in the Age of Foundation Models at NeurIPS and co-edited the workshop proceedings.
- 2020–2023Co-organized the ICML Workshop on Computational Biology.
Based in New York City. Outside work: vinyl, jazz, bouldering, and photography.