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Yuzhou Chang

Department of Biomedical Informatics, College of Medicine
The Ohio State University
2255 Kenny Rd, Columbus, OH 43210
Email: yuzhou.chang@osumc.edu | chang.1754@osu.edu | ychang13@bidmc.harvard.edu
GitHub: BMEngineeR

Education

• Postdoc (01/2024 – Present)
  Joint Postdoctoral Researcher
  • Immuno-Oncology Informatics Group, Pelotonia Institute for Immuno-Oncology, The Ohio State University
    
  • Beth Israel Deaconess Medical Center, Harvard Medical School
• Ph.D. (08/2018 – 12/2023)
  Biomedical Sciences Graduate Program, The Ohio State University
  • Advisors: Prof. Qin Ma, Prof. Zihai Li
    
  • Training: Statistical modeling, bioinformatics, computational system biology
• B.E. (09/2012 – 06/2016)
  Biopharmaceutical, China Pharmaceutical University
  • Advisor: Weihua Chu

Honors & Awards

• ICIBM 2023 Student & Trainee Travel Award (07/2023)
  
• Award for Excellence in Research (Graduate Student) (12/2021)
  
• Outstanding Student Leader (3 times: 09/2013–09/2015)
  
• Second-Class Scholarship (09/2015)

Research Interests

• Graph signal processing for spatial transcriptomics.
  
• Developing computational tools for spatial omics data analysis, including cell-cell communication and tissue architecture identification based on deep learning.
  
• Applying spatial transcriptomics to immuno-oncology.
  
• Gene regulatory network inference.

Research & Work Experience

Graduate Research Assistant

Qin Ma Lab, The Ohio State University (04/2019 – 12/2023)
- Spatial transcriptomics analysis.
- Gene regulatory network inference.
- scRNA-Seq data analysis.
- Methylation data analysis.

Student Trainee

Illumina, Shanghai, China (01/2017 – 06/2018)
- RNA-seq library preparation and sequencing quality control.
- BaseCalling to FASTQ transformation.

Research Assistant

Chu’s Lab, China Pharmaceutical University (09/2016 – 12/2016)
- Performed experiments: microbial culture, drug-sensitivity testing, and DNA extraction.

Tool Development

• SpaGFT: Spatial omics feature representation based on Graph Fourier Transform (doc).
  
• RESEPT: A deep learning framework for tissue architecture identification based on spatial transcriptomics data (GitHub).
  
• SPRUCE: Bayesian multivariate mixture model for spatial transcriptomics data (GitHub).
  
• IRIS-FGM: An integrative single-cell RNA-Seq interpretation system for functional module analysis (Bioconductor).
  
• scGNN: Single-cell Graph Neural Network (GitHub).

For a full list of publications, visit Google Scholar.

CV