Autonomous AI Predictive Analytics Platform

End-to-end customer churn prediction project using the Telco dataset. Includes EDA, data preprocessing, Logistic Regression / Random Forest / XGBoost model comparison, SHAP explainability, and a production-ready prediction pipeline.

MultiModal Disaster Response System — BERT + ResNet-50 fusion for real-time disaster intelligence

This project employs Logistic Regression for binary classification, to predict whether a borrower is capable of repaying a loan based on various financial and demographic factors.

Spatio-temporal graph deep learning for IPL T20 match outcome prediction. GAT player-interaction graph + BiLSTM + cross-attention Transformer. Ball-by-ball win probability, run forecasting & Player Impact Score with SHAP explainability.

Real-time PPG-based atrial fibrillation detection using Random Forest with feature-level explainability and interactive visualization.

LangGraph-based agent pipeline for code evaluation using static analysis, FAISS-powered RAG, and LLMs with SHAP-style explainability.

Enterprise-grade Android threat intelligence platform combining static APK analysis (Androguard), dynamic sandboxing (Frida), LLM-powered behavioral assessment (Gemini 2.0), and explainable ML (XGBoost + SHAP). Features real-time streaming analysis, India-specific banking trojan detection, multi-dimensional risk scoring, and compliance-ready audit

ML-powered crop yield prediction for Maharashtra — Gradient Boosting (R²=0.977), SHAP explainability, MLflow experiment tracking, LLM-powered AI explanations, and interactive Streamlit dashboard.

The AI Loan Analyst is a sophisticated Streamlit-based web application designed to automate and enhance the loan analysis process for financial institutions. It combines data science, machine learning, and financial modeling to provide a complete loan portfolio management solution.

I built this application to allow users to input various clinical parameters and receive an instant prediction of whether a patient is likely to have CKD. The app is hosted on Streamlit community cloud for public access.

Built a machine learning model to predict telecom customer churn using classification techniques and SHAP explainability. Optimized performance through tuning and translated results into actionable customer retention insights.

ML-based beta thalassemia carrier screening from CBC parameters for Sri Lankan primary care. SVM + SHAP explainability, MOH referral letters, couple screening, voice input, and analytics dashboard.

FraudDetectAI is an advanced credit card fraud detection system built with XGBoost and Hybrid SMOTE Sampling (Oversampling + Undersampling). This project tackles highly imbalanced datasets, ensuring strong fraud detection accuracy while minimizing overfitting risks.