About Me

I am a 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. My current research focuses on the intersection of bioinformatics, translational research and AI/ML to advance the drug development for neurodegenerative diseases.

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!