Graduate student in Data Science at INTI International University, Malaysia. I build ML models, data pipelines, and web applications — with a focus on healthcare analytics and fisheries economics.
Developing unsupervised ML models (Isolation Forest, LOF, One-Class SVM) for anomaly detection in healthcare claims data as part of my MSc thesis.
Data & ML: Python, SQL, scikit-learn, pandas, NumPy
Analytics & BI: KNIME, Matplotlib, Seaborn
Development: Git, Jupyter Notebook, Google Colab, Flask
Databases: MySQL, Neo4j (graph databases)
Domains: Healthcare analytics, retail forecasting, fisheries prediction
- Healthcare Anomaly Detection — Comparing Isolation Forest, LOF, and OCSVM for fraud detection in Medicare claims (thesis-related)
- Malaysian Fish Landings Forecasting — XGBoost, LSTM, and statistical models to forecast fish landings through 2030 with climate features
- Tuna Bycatch Analysis — Multi-phase WCPFC bycatch data analysis: diagnostics, transparent metrics, Bayesian sensitivity
- Retail Sales Prediction — Time series forecasting for retail business planning
- Smart Car Rental System — Flask web app with user booking, admin dashboard, and payment workflow
- EHR Consent Prototype — Front-end skeleton for blockchain-based EHR consent management using ethers.js (demo only)
- IBM Data Science Professional Certificate (Coursera)
- IBM Data Analyst Professional Certificate (Coursera)
- Meta Data Analyst Professional Certificate (Coursera)
- 📍 Malaysia
- 🎓 MSc Data Science | INTI International University
- 🔬 Research: Anomaly detection in healthcare claims