Hany A.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

I build AI and computational solutions for biomedical research, combining clinical expertise, bioinformatics, machine learning, and software engineering. I’m an AI & Bioinformatics Data Scientist with a background in pharmacy, bioinformatics, clinical data science, AI/ML, and software engineering. My work sits at the intersection of: Biomedical AI • Bioinformatics • Clinical Data Science • Multi-Omics • Cancer Research • Pharmacovigilance • Drug Discovery • Computational Biology What I do 🧬 Bioinformatics & Multi-Omics * Transcriptomics and RNA-seq analysis * Cancer genomics and molecular profiling * Multi-omics integration * Single-cell and spatial omics workflows * Machine learning for biological data * Network and graph-based analysis * Reproducible computational pipelines 🏥 Clinical AI & Medical Data Science * Clinical prediction modeling * Real-world clinical data analysis * Pharmacovigilance * Epidemiological analysis * Patient/outcome profiling * Propensity-score and causal inference methods * Explainable AI and model validation 🧪 AI for Drug Discovery * QSAR/QSPR * Molecular machine learning * Virtual screening * Computational drug discovery * Protein and peptide analysis * Molecular property prediction * AI-assisted therapeutic design 🤖 Machine Learning & AI * Python * PyTorch * scikit-learn * Deep learning * Graph neural networks * NLP * LLM-powered applications * Feature engineering * SHAP and explainability * Statistical learning ⚙️ Engineering & Production * Python data and ML pipelines * APIs and backend systems * SQL * Docker * Git/GitHub * Linux * FastAPI * AI-powered research applications What makes my approach different I don't treat biomedical projects as purely coding problems. My background allows me to understand the biological or clinical question, translate it into a rigorous computational problem, develop the analysis or AI model, evaluate it appropriately, and turn the work into a reproducible computational solution. My goal is to bridge: Biological question → Data → Statistical/AI model → Validation → Reproducible pipeline → Usable solution I can work with researchers, biotech and pharmaceutical teams, health-tech companies, scientific startups, and organizations building AI-enabled biomedical products. Typical projects * Biomedical machine learning * Cancer multi-omics * Bioinformatics pipelines * Clinical prediction models * Pharmacovigilance * Drug discovery AI * Computational biology * Scientific data analysis * Research-grade ML * Biomedical AI applications If you have a biomedical dataset, research question, AI problem, or computational drug-discovery challenge, I can help turn it into a rigorous and reproducible solution.