SHAHID||Portfolio
A collection of end-to-end AI systems and analytical platforms designed to solve high-stakes challenges.
An open-source ML reliability and diagnostics framework for evaluating model trustworthiness beyond accuracy. Analyzes calibration, fairness, failure patterns, and deployment risk using a unified API.
Engineered a high-precision deep learning model using PyTorch to classify respiratory diseases from chest X-rays with state-of-the-art accuracy.
An Integrated eXplainable Clinical Decision Support System (X-CDSS) for Precision Cardiovascular Risk Assessment using SHAP and XGBoost.
Developed a predictive diagnostic tool using Scikit-learn, deploying the model via a professional Streamlit command center for real-time support.
An interactive sales intelligence dashboard using Dash & Plotly to visualize historical trends and forecast future product demand cycles.
Architected a secure database platform to manage criminal records, implementing full CRUD with optimized SQL systems.