About Me

I am an incoming bioinformatics scientist at Bristol Myers Squibb, and a PhD alumni of The University of Texas MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences.

Contact & Links

• Email: liuwd15@gmail.com
• LinkedIn: wendao-liu
• GitHub: liuwd15
• Google Scholar: View Profile

Research Interests

My research focuses on developing computational methods for understanding biological systems and analyzing large-scale omics for human disease research:

• Computational methods: Machine learning applications in biology, foundation models for omics data
• Single-cell and spatial biology: Transcriptomics, multi-omics integration
• Immune cell states: T cell receptor sequencing, immune cell polarization, and functional states
• Neurodegenerative disease: Alzheimer’s disease pathology, neuroinflammation, and drug development
• Cancer immunology: Tumor microenvironment analysis, cancer immunotherapies, therapeutic target identification
• Previous Experience: Collaborative research across computational biology, clinical medicine, and animal experiments

Technical Skills

• Agent-assisted research and programming: Claude Code, Codex, Github Copilot
• Machine learning skills: Pytorch, Pytorch Lightling, Scikit-learn, Captum, Ray
• Programming language skills: Python, R, Bash, C, C++, Java, SQL
• Software development: Git & Github, Conda, Docker, R & Python package
• Statistic skills: Frequentist & Bayesian inference, Generative models, MCMC, Variational inference
• Biological foundation models: DNA models (Enformer, DNABert, Evo, AlphaGenome), protein models (AlphaFold, ESM, RoseTTAFold/RFDiffusion), single-cell models (scGPT, scFoundation, UCE, SCimilarity)
• Omics data analysis: DNA-seq, RNA-seq, ATAC-seq, TCR/BCR-seq, single-cell multiome, spatial transcriptomics, proteomics
• Single-cell and spatial transcriptomics tools: Scanpy, Scvi-tools, Pertpy, Scirpy, Squidpy, SpatialData, Seurat, Signac, etc
• Linux skills: Hardware & software configuration, Slurm system, AWS cloud computing
• Flow cytometry analysis: FlowJo

💻 Software & Tools

I develop and maintain several open-source bioinformatics tools:

• Turep: Cross-cancer tumor-reactive CD8+ T cell prediction
• FADVI: Disentangled representation learning for single-cell and spatial omics data integration
• irvi: Joint analysis of gene expression and T-cell receptor (TCR) sequence data
• Scupa: Single-cell unified polarization assessment of immune cells using foundation models
• GAN-DP: StyleGAN2-based method to create semantic image-driven phenotypes
• tomoda: R/Bioconductor package for tomo-seq data analysis
• sc-miReg: Analysis of miRNA regulation in single cells
• scRIN: Measuring mRNA integrity in single-cell sequencing data

Interested in collaboration or have questions about my research tools? Feel free to reach out!