Muhammad Haider Shahbaz

I've built genomic analysis pipelines and computational drug-discovery workflows through internships at NIBGE and the Centre of Agricultural Biochemistry and Biotechnology at UAF. At CABB, I developed a tumor-normal somatic variant-calling pipeline spanning alignment, MAF generation, VEP annotation, COSMIC/OncoKB cross-referencing, and maftools visualization.

My work combines NGS analysis, automation, and applied machine learning. I have analyzed cattle sequencing data with PLINK and GWAS, co-authored obesity-risk research comparing eight machine-learning models, and built an explainable antimicrobial-peptide classifier using XGBoost, SHAP, and ESM-2 embeddings.

I'm focused on bringing computational genomics and pipeline engineering to clinical diagnostics and biotech R&D, while continuing to work across structural biology, molecular docking, genome assembly, and reproducible high-throughput workflows.