Xin Tang, University of British Columbia

Research

Ai For Cancer Genomics Bioinformatics Cd24/Cd24a Immune Evasion Immune-Cold Tumours Interpretable Ai Machine Learning For Biomedicine Mesenchymal Stromal Cells

Latest funding

PerturbKAN: Interpretable and Informed Machine Learning Model for Gene Perturbation using Kolmogorov-Arnold Networks
CIHR · 2026 · Supervisor
$27,000
Deciphering Immune Evasion in Synovial Sarcoma through Interpretable AI and Validation Experiments
CIHR · 2026 · Nominated PI
$948,600
Deciphering Immune Evasion in Synovial Sarcoma through Interpretable AI and Validation Experiments
CIHR · 2026 · Nominated PI
$25,000

All 3 grants and awards

PerturbKAN: Interpretable and Informed Machine Learning Model for Gene Perturbation using Kolmogorov-Arnold Networks

SupervisorCIHR2026CIHR Strategic Master's Award - Bioinformatics, Comput. Biology/Health Data Sci.

Principal investigators: He-Mo, Alex

Keywords: Computational Biology; Deep Learning; Explainable Artificial Intelligence; Gene Perturbation; Gene Regulatory Networks; Genomics And Transcriptomics; Single-Cell Rna Sequencing; Systems Biology

$27,000

Deciphering Immune Evasion in Synovial Sarcoma through Interpretable AI and Validation Experiments

Nominated PICIHR2026Project Grant

Principal investigators: Tang, Xin; Underhill, Michael

Keywords: Ai For Cancer Genomics; Bioinformatics; Cd24/Cd24a; Immune Evasion; Immune-Cold Tumours; Interpretable Ai; Machine Learning For Biomedicine; Mesenchymal Stromal Cells; Single-Cell And Spatial Omics; Synovial Sarcoma

$948,600

Deciphering Immune Evasion in Synovial Sarcoma through Interpretable AI and Validation Experiments

Nominated PICIHR2026PRIZE - Project Grant - PA: Prize: Early Career Investigator in Cancer

Principal investigators: Tang, Xin

Keywords: Ai For Cancer Genomics; Bioinformatics; Cd24/Cd24a; Immune Evasion; Immune-Cold Tumours; Interpretable Ai; Machine Learning For Biomedicine; Mesenchymal Stromal Cells; Single-Cell And Spatial Omics; Synovial Sarcoma

$25,000

From CIHR, NSERC and SSHRC funding decisions: CIHR since 2008, NSERC since 1991 and SSHRC since 1998, including their latest published competition results.

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Applying for

Mention their CIHR grant from 2026

Subject: Prospective PhD student: Ai For Cancer Genomics Dear Professor Tang, My name is [your name], and I am a [your current degree or role] at [your institution]. I am applying for a PhD position starting in [term and year]. Your research on ai for cancer genomics connects closely to my own work on [your research topic]. [One or two sentences on what you did and what you learned.] I also saw your CIHR-funded project "Deciphering Immune Evasion in Synovial Sarcoma through Interpretable AI and Validation Experiments" (2026), and I would be glad to contribute to work in that direction. Are you accepting new PhD students for [term and year]? I have attached my CV and transcripts, and I would be glad to talk at a time that suits you. Thank you for your time. Kind regards, [your name]